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Abstract: { We consider evaluating the causal effects of dynamic treatments, i.e.\ of multiple treatment sequences in various periods, based on double machine learning to control for observed, time-varying covariates in a data-driven way under a selection-on-observables assumption. To this end, we make use of so-called Neyman-orthogonal score functions, which imply the robustness of treatment effect estimation to moderate (local) misspecifications of the dynamic outcome and treatment models. This robustness property permits approximating outcome and treatment models by double machine learning even under high dimensional covariates and is combined with data splitting to prevent overfitting. In addition to effect estimation for the total population, we consider weighted estimation that permits assessing dynamic treatment effects in specific subgroups, e.g.\ among those treated in the first treatment period. We demonstrate that the estimators are asymptotically normal and $\sqrt{n}$-consistent under specific regularity conditions and investigate their finite sample properties in a simulation study. Finally, we apply the methods to the Job Corps study in order to assess different sequences of training programs under a large set of covariates.
}
{ Keywords: dynamic treatment effects, double machine learning, efficient score.}
{ JEL classification: C21. \quad }
{ {\scriptsize We have benefited from comments by Jelena Bradic, Saraswata Chaudhuri, Yingying Dong, Arturas Juodis, Frank Kleibergen, Jonathan Roth, Vasilis Syrgkanis, Davide Viviano, and seminar participants at McGill University, the University of Amsterdam, the University of Duisburg-Essen, the University of Bolzano/Bozen, and the University of California Irvine (all online).
Addresses for correspondence: Hugo Bodory, University of St.\ Gallen, Varnb\"{u}elstrasse 14, 9000 St.\ Gallen, Switzerland, [email removed]; Martin Huber, University of Fribourg, Bd.\ de P\'{e}rolles 90, 1700 Fribourg, Switzerland, [email removed]; Luk\'{a}\v{s} Laff\'{e}rs, Matej Bel University, Tajovskeho 40, 97411 Bansk\'{a} Bystrica, Slovakia, [email removed]. Laff\'{e}rs acknowledges support provided by the Slovak Research and Development Agency under contract no. APVV-17-0329 and VEGA-1/0692/20.
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Introduction
In many empirical problems, policy makers and researchers are interested in the causal effects of sequences of interventions or treatments, i.e.\ dynamic treatment effects. Examples include the impact of sequences of training programs (for instance, a job application training followed by a language courses) on the employment probabilities of job seekers or the effect of sequential medical interventions (for instance,a surgery combined with rehabilitation training) on health. As treatment assignment is typically non-random, causal inference about distinct sequences of treatments requires controlling for confounders jointly affecting the various treatments and the outcome of interest. An assumption commonly imposed in the literature is sequential conditional independence, which implies that the treatment in each period is unconfounded conditional on past treatment assignments, past outcomes, and the history of observed covariates up to the respective treatment assignment. Due to increasing data availability, the number of observed covariates that may potentially serve as control variables to justify the sequential conditional independence assumption has been growing in many empirical contexts, which poses the question of how to optimally control for such a wealth of information in the estimation process.
This paper combines the semiparametrically efficient estimation of dynamic treatment effects under sequential conditional independence with double machine learning (DML) framework outlined in Chetal2018 to control for observed covariates in a data-driven way. More specifically, treatment effect estimation is based on the efficient score function, belonging to the class of doubly robust estimation as discussed in Robins+94 and RoRo95, and relies on plug-in estimates of the dynamic treatment propensity scores (the conditional treatment probabilities given histories of covariates and past treatments) and conditional mean outcomes (given histories of treatments, covariates, and past outcomes). We obtain these plug-in estimates by machine learning, which permits algorithmically controlling for covariates with the highest predictive power for the treatments and outcomes.
To safeguard against overfitting bias due to correlations between the estimation steps, the plug-in models and the treatment effects are estimated in different parts of the data, whose role is subsequently swapped to prevent not using parts of the data for effect estimation (and thereby increasing the variance). We show that our estimator satisfies the so-called Neyman1959 orthogonality discussed in Chetal2018 and is thus asymptotically normal and $\sqrt{n}$-consistent under specific regularity conditions despite the data-driven estimation of the plug-ins. One restriction is that the convergence of the plug-in estimates to the true models as a function of the covariates is not too slow, which is satisfied if each of the estimators converges at a rate not slower than $n^{-1/4}$. When using lasso as machine learner, this implies a form of approximate sparsity, meaning that the number of important covariates for obtaining a decent approximation of the plug-ins is small relative to the sample size. However, the set of these important confounders need not be known a priori, which is particularly useful in high dimensional data with a vast number of covariates that could potentially serve as control variables.
As a further contribution, we discuss the DML-based estimation of weighted dynamic treatment effects where the weight is defined as a function of the baseline covariates. This permits, for instance, assessing treatment sequences among those treated or not treated in the first period and therefore provides a rather general framework for the definition of interesting subpopulations. Also for this estimator based on a weighted version of the efficient sore function, we show Neyman1959 orthogonality and $\sqrt{n}$-consistency under specific restrictions on the convergence rates of the plug-in estimators, which now also include the estimated weighting function.
Furthermore, we investigate the methods' finite sample behavior in a simulation study, and find the point estimators to perform rather decently in the simulation designs considered. As an empirical contribution, we assess the effects of various treatment sequences in the U.S.\ Job Corps study on an educational intervention for disadvantaged youth. We find that attending vocational training in the two initial years of the program likely increases the employment probability four years after the start of Job Corps when compared to no instruction. In contrast, the relative performance of sequences of vocational vs.\ academic classroom training is less clear.
The literature on dynamic treatment effects goes back to Ro86, who proposes a dynamic causal framework along with an estimation approach known as g-computation for recursively modeling outcomes at some point in time as functions of the (histories of) observed covariates and treatments under the sequential conditional independence assumption.
G-computation was originally implemented by parametric maximum likelihood estimation of nested structural models for the outcomes in all periods, requiring the (in general tedious) estimation of the conditional densities of all time-varying covariates. Robins1998 suggested an alternative, less complex modeling approach based on so-called marginal structural models representing outcomes in specific treatment states as functions of time-constant covariates only. In order to also control for time-varying confounding, such marginal models need (in the spirit of HoTh52) to be combined with weighting by the inverse of the dynamic treatment propensity scores, see for instance RoGrHu1999 and RoHeBr00. The propensity scores in each period are typically estimated by sequential logit regressions, but see ImaiRatkovic2015 for an alternative, empirically likelihood-based approach that aims at finding propensity score specifications that maximize covariate balance. Lech09 considers inverse probability weighting (IPW) by the dynamic treatment propensity scores alone (i.e. without the use of marginal outcome models), while LechnerMiquel2010 apply propensity score matching and BlackwellStrezhnev2020 direct matching on the covariates.
Doubly robust estimators of dynamic treatment effects comprise methods that are consistent if either the sequential treatment propensity scores or nested outcome models are correctly specified. This includes estimation based on the sample analog of the efficient influence function (underlying the semiparametric efficiency bounds) provided in Robins1999, which is a function of both the nested treatment and outcome models.\footnote{YU20061061 discuss an alternative doubly robust approach based on combining propensity scores with the estimation of marginal structural models.} In contrast, BaRo05 propose a doubly robust estimator that is based on estimating potential outcomes by nested models of conditional mean outcomes (given the covariate histories as well as past and current treatment assignments) in all periods, a form of g-computation that does not require tedious likelihood estimations of conditional densities as initially proposed in Ro86. Here, doubly robustness comes from the fact that a weight based on the nested treatment propensity scores is included as additional covariate in conditional mean estimation.
TargetedMinimumLossBasedEstimation demonstrate that this approach fits the framework of Targeted Maximum Likelihood Estimation (TMLE) of vanderLaanRubin2006, which obtains doubly robustness through updating initial conditional outcome estimates by regressing them on a function of the nested propensity scores in each period, and offer a refined estimator. Specifically, they suggest estimating nuisance parameters by the super learner of vanderLaanetal2007, an ensemble method for machine learning. In contrast, the approach suggested in this paper does not rely on the likelihood estimation of marginal structural models, nor of nested structural models requiring the estimation of conditional covariate densities. Similar to TMLE, our approach is based on combining nested conditional mean outcomes with propensity score estimation. Different to TMLE, however, we base estimation on the efficient influence function, which does not iteratively update the nested outcomes. In addition, we also consider weighted treatment effect estimation as a function of baseline covariates. As we estimate the plug-in parameters by machine learning as recently also considered in Tranetal2019, we formally show that our approach fits the double machine learning framework of Chetal2018 and discuss regularity conditions under which $\sqrt{n}$-consistency is attained.
LewisSyrgkanis2020 propose an alternative DML estimator of dynamic treatment effects. It is based on residualizing or debiasing the outcome and the treatment by purging the effects of observed confounders using machine learning and regressing the debiased outcome on the debiased treatment in a specific period. This approach may also be applied to continuous (rather than discrete) treatments, but in contrast to our method assumes partial linearity in the outcome model. Finally, VivianoBradic2021 suggest a further doubly robust method that can be combined with machine learning, but replaces weighting by the inverse of the propensity scores (as applied in our paper) by a dynamic version of covariate balancing as discussed in Zubizarreta2015 and AtheyImbensWager2018.
This paper proceeds as follows. Section (ref) introduces the concepts of dynamic treatment effects in the potential outcome framework,
presents the identifying assumptions and discusses identification. Section (ref) proposes an estimation procedure based on double machine learning and shows $\sqrt{n}$-consistency and asymptotic normality under specific conditions. Section (ref) extends the procedure to the evaluation of weighted dynamic treatment effects.
Section (ref) provides a simulation study. Section (ref) presents an empirical application to data from Job Corps, an educational program for disadvantaged youth. Section (ref) concludes.
Definition of dynamic treatment effects and identification
We are interested in the causal effect of a sequence of discretely distributed treatments and will for the sake of simplicity focus on the case of two sequential treatments in the subsequent discussion. To this end, denote by $D_t$ and $Y_t$ the treatment (e.g a training program) and the outcome (e.g. employment) in period $T=t$. Therefore, $D_1$ and $D_2$ are the treatments in the first and second periods, respectively, and may take values $d_1,d_2$ $\in$ $\{0,1,...,Q\}$, with $0$ indicating non-treatment and $1,...,Q$ the different treatment choices (where $Q$ denotes the number of non-zero treatments). Let $Y_2$ denote the outcome of interest measured in the second period after the realization of treatment sequence $D_1$ and $D_2$.\footnote{We do not consider the evaluation of treatment effects on outcomes in the first period, as this corresponds to the conventional static treatment framework as for instance considered in Chetal2018.} To define the dynamic treatment effects of interest, we make use of the potential outcome framework, see for instance Rubin74. We denote by $\underline{d}_2$ a specific treatment sequence $(d_1,d_2)$ with $d_1,d_2$ $\in$ $\{0,1,...,Q\},$ then $\underline{D}_2 \equiv (D_1,D_2)$ and let $Y_2(\underline{d}_2)$ denotes the potential outcome hypothetically realized when the treatments are set to that sequence $\underline{d}_2$. We also define $\{0,1,...,Q\}^2 = \{0,1,...,Q\} \times \{0,1,...,Q\}$.
We aim at evaluating the average treatment effect (ATE) of two distinct treatment sequences in the population,
eqnarray[eqnarray omitted — 105 chars of source]
with $\underline{d}_2\neq\underline{d}^*_2$ such that the sequences differ either in $d_1$ or in both $\underline{d}_2$.\footnote{In the case of $\underline{d}_2,\underline{d}^*_2$ sharing the same $d_1$ but differing in terms $d_2$, the identification problem collapses to the standard case with one treatment period (namely $T=2$) under the condition that $D_1=d_1$. The case of a single treatment period also prevails when considering the effects on $Y_1$, i.e.\ the outcome in period $T=1$, which only permits assessing the effect of $D_1$. In either case, the standard double machine learning (DML) framework for single treatment periods can be applied as e.g.\ outlined in Bellonietal2017, such that we do not consider these scenarios in this paper.} Examples are the evaluation of a sequence of two binary treatments vs. no treatment, e.g.\ $\underline{d}_2= (1,1)$ and $\underline{d}^*_2=(0,0)$, or the effect of the first treatment when holding the second treatment constant, $\underline{d}_2=(1,d_2)$ and $\underline{d}^*_2=(0,d_2)$, with $d_2$ $\in$ $\{0,1\}$. The latter parameter is known as the controlled direct effect in causal mediation analysis, see for instance Pearl01, assessing the net effect of the first treatment when setting the second treatment to be $D_2=d_2$ for everyone.\footnote{From the perspective of causal mediation analysis, our paper complements the study of Farbmacheretal2020, who apply DML to the estimation of so-called natural direct and indirect effects. In the latter case, $D_2$ is not prescribed to have the same value $d_2$ for everyone, but corresponds to the potential value $D_2(d_1)$, i.e.\ the hypothetical treatment state of $D_2$ that would be `naturally chosen' (i.e.\ without prescription) as a consequence of $D_1=d_1$.} Throughout the paper we assume that stable unit treatment value assumption (SUTVA, Rubin80) holds such that $\Pr(\underline{D}_2 = \underline{d}_2 \implies Y_2 = Y_2(\underline{d}_2))=1.$ This rules out interaction effects, general equilibrium effects and implicitly assumes that treatments are uniquely defined.
figure[figure omitted — 177 chars of source]
Identification relies on a sequential conditional independence assumption, requiring that the treatment in each period is conditionally independent of the potential outcomes, conditional on previous treatments and (histories of) observed covariates measured prior to treatment, which might include past outcomes, too. Let to this end $X_t$ denote the observed characteristics in period $T=t$. $X_0$ consists of pre-treatment characteristics measured prior to the first treatment $D_1$, while $X_1$ (which may contain $Y_1$) is measured prior to $D_2$, but may be influenced by $D_1$ as well as $X_0$. Covariates in a particular period may therefore be affected by previous covariates and treatments, implying that confounding may be dynamic in the sense that identification relies on time varying observables rather than on baseline covariates alone. Figure (ref) provides a graphical illustration using a directed acyclic graph, with arrows representing causal effects. Each of $D_1$, $D_2$, and $Y_2$ might be causally affected by distinct and statistically independent sets of unobservables not displayed in Figure (ref), but none of these unobservables may jointly affect $D_1$ and $Y_2$ given $X_0$ or $D_2$ and $Y_2$ given $D_1$, $X_0$, and $X_1$.
Formally, the first assumption invokes conditional independence of the treatment in the first period $D_1$ and the potential outcomes $Y_2(\underline{d}_2)$ given $X_0$ as commonly invoked in the treatment evaluation literature, see e.g.\ Imbens03. It rules out unobserved confounders jointly affecting $D_1$ and $Y_2(\underline{d}_2)$ conditional on $X_0$.
\newline
Assumption 1 (conditional independence of the first treatment):\newline
$Y_2(\underline{d}_2) \bot D_1 | X_0$, for $\underline{d}_2$ $\in$ $\{0,1,...,Q\}^2$.\newline
where `$\bot$' denotes statistical independence.
\newline
The second assumption invokes conditional independence of the second treatment $D_2$ given the first treatment $D_1$ and the (history of) covariates $X_0$ and $X_1$, which we denote by $\underline{X}_1=(X_0,X_1)$ to ease notation. It rules out unobserved confounders jointly affecting $D_2$ and $Y_2(\underline{d}_2)$ conditional on $D_1$ and $\underline{X}_1$.
\newline
Assumption 2 (conditional independence of the second treatment):\newline
$Y_2(\underline{d}_2) \bot D_2 | D_1, X_0, X_1$, for $\underline{d}_2$ $\in$ $\{0,1,...,Q\}^2$. \newline
\newline
The third assumption imposes common support, meaning that the treatment in each period is not a deterministic function of the respective observables in the conditioning set, which rules out conditional treatment probabilities (or propensity scores) of $0$ or $1$. This implies that conditional on each value of the observables occuring in the population, subjects with distinct treatment assignments $\{0,1,...,Q\}$ exist.
\newline
Assumption 3 (common support):\newline
$\Pr(D_1=d_1| X_0)>0$, $\Pr(D_2=d_2| D_1, \underline{X}_1)>0$ for $d_1, d_2$ $\in$ $\{0,1...,Q\}$.\newline
To ease notation, we henceforth denote the propensity scores by $p^{d_1}(X_0)=\Pr(D_1=d_1|X_0)$ and $p^{d_2}(D_1,\underline{X}_1)=\Pr(D_2=d_2|D_1,\underline{X}_1)$. Furthermore, we denote the conditional mean outcome in the second period by $\mu^{Y_2}(\underline{D}_2,\underline{X}_1)=E[Y_2|\underline{D}_2,X_0,X_1]$ and the nested conditional mean outcome in the first period by
eqnarray[eqnarray omitted — 121 chars of source]
where $F_{X_1=x_1|D_1,X_0}$ denotes the conditional distribution function of $X_1$ given $(D_1,X_0)$ at value $x_1$.
For a fixed vector of treatments $\underline{D}_2=\underline{d}_2$ the quantity $\nu^{Y_2}(\underline{d}_2,X_0)$ is equal to $E[E[Y_2|\underline{D}_2=\underline{d}_2,X_0,X_1]|D_1=d_1,X_0]$, and this suggests that it can be obtained by a sequential estimation of nested conditional means.
This is the approach followed in this paper, as it avoids the estimation of conditional covariate distributions, which might be cumbersome if covariates are high dimensional.
As for instance discussed in Tranetal2019, Assumptions 1-3 permit identifying the mean potential outcome $E[Y(\underline{d}_2)]$ based on the following expression:
eqnarray[eqnarray omitted — 433 chars of source]
This follows from the fact that $\psi^{\underline{d}_2}-E[Y(\underline{d}_2)]$, which corresponds to the efficient score function of dynamic treatment effects as discussed in Robins1999, has a zero mean property: $E[\psi^{\underline{d}_2}-E[Y(\underline{d}_2)]]=0$.
Estimation of the counterfactual with K-fold Cross-Fitting
We subsequently propose an estimation strategy for the counterfactual $E[Y(\underline{d}_2)]$ with $\underline{d}_2 \in \{0,1,...,Q\}^2$ and show its $\sqrt{n}$-consistency under specific regularity conditions. Define
eqnarray[eqnarray omitted — 428 chars of source]
where $\mathcal{W} = \{W_i|1\leq i \leq N\}$ with $W_i = (Y_{2i}, D_{1i}, D_{2i}, X_{0i},X_{1i})$ for all $ i $ denotes the set of observations and $I\{\cdot\}$ denotes the indicator function.
The true nuisance parameters are denoted by $\eta_0=(p_0^{d_1}(X_0), p_0^{d_2}(D_1,\underline{X}_1),\mu_0^{Y_2}(\underline{D}_2,\underline{X}_1), \nu_0^{Y_2}(\underline{D}_2,X_0))$, their estimates by \newline
$\hat{\eta}=(\hat{p}^{d_1}(X_0), \hat{p}^{d_2}(D_1,\underline{X}_1), \hat{\mu}^{Y_2}(\underline{D}_2,\underline{X}_1), \hat{\nu}^{Y_2}(\underline{D}_2,X_0))$. Let $\Psi^{\underline{d}_2}_{0}=E[Y(\underline{d}_2)]$ denotes the true counterfactual.
We suggest estimating the $\Psi^{\underline{d}_2}_{0}$ using the following algorithm that combines orthogonal score estimation and sample splitting. Further below we will outline the conditions under which this estimation strategy leads to $\sqrt{n}$-consistent estimates for the counterfactual. \newline
Algorithm 1: Estimation of $E[Y(\underline{d}_2)]$
enumerate• Split $\mathcal{W}$ in $ K $ subsamples. For each subsample $ k $, let $n_k$ denote its size, $\mathcal{W}_k$ the set of observations in the sample and $\mathcal{W}_k^{C}$ the complement set of all observations not in $k$.
• For each $k$, use $\mathcal{W}_k^{C}$ to estimate the model parameters of $p^{d_1}(X_0)$ and $p^{d_2}(d_1,\underline{X}_1)$. Split $\mathcal{W}_k^{C}$ into 2 non-overlapping subsamples and estimate the model parameters of the conditional mean $\mu^{Y_2}(\underline{d}_2,\underline{X}_1)$ and the nested conditional mean $\nu^{Y_2}(\underline{d}_2,X_0)$ in the distinct subsamples. Predict the models among $\mathcal{W}_k$, where the predictions are denoted by $\hat{p}_k^{d_1}(X_0)$, $\hat{p}_k^{d_2}(D_1,\underline{X}_1)$, $\hat{\mu}_k^{Y_2}(\underline{d}_2,\underline{X}_1)$, $\hat \nu_k^{Y_2}(\underline{d}_2,X_0)$.
• For each $ k $, obtain an estimate of the moment condition for each observation $i$ in $\mathcal{W}_k$, denoted by $\hat \psi^{\underline{d}_2}_{i,k}$ :
\begin{eqnarray}
\hat \psi^{d_2}_{i,k}&=& \frac{I\{D_{1i}=d_1\} \cdot I\{D_{2i}=d_2\} \cdot [Y_{2i}-\hat\mu_k^{Y_2}(d_2,X_{1i})]}{\hat p_k^{d_1}(X_{0i})\cdot \hat p_k^{d_2}(d_1,X_{1i})} \notag\\
& + &\frac{I\{D_{1i}=d_1\}\cdot [\hat \mu_k^{Y_2}(d_2,X_{1i})-\hat \nu_k^{Y_2}(\underline{d}_2,X_{0i})]}{\hat p_k^{d_1}(X_{0i})} +\hat \nu_k^{Y_2}(\underline{d}_2,X_{0i}).\notag
\end{eqnarray}
• Average the estimated scores $\hat \psi^{\underline{d}_2}_{i,k}$ over all observations across all $ K $ subsamples to obtain an estimate of $\Psi^{\underline{d}_2}$ in the total sample, denoted by $\hat \Psi^{\underline{d}_2}=1/n \sum_{k=1}^{K} \sum_{i=1}^{n_k} \hat \psi^{\underline{d}_2}_{i,k}$.
As a remark concerning step 2 of the algorithm, it may appear non-standard to estimate $\mu^{Y_2}(\underline{d}_2,\underline{X}_1)$ and $\nu^{Y_2}(\underline{d}_2,X_0)$ in distinct subsamples. This approach aims at avoiding correlations between both estimation steps and thus, overfitting bias, because the estimate of $\mu^{Y_2}(\underline{d}_2,\underline{X}_1)$ is used as a plug-in parameter for estimating $\nu^{Y_2}(\underline{d}_2,X_0)$.
In order to achieve $\sqrt{n}$-consistency for counterfactual estimation, we make the following assumption on the prediction quality of the machine learners when estimating the nuisance parameters. Closely following Chetal2018, we introduce some further notation. Let $(\delta_n)_{n=1}^{\infty}$ and $(\Delta_n)_{n=1}^{\infty}$ denote sequences of positive constants with $\lim_{n\rightarrow \infty} \delta_n = 0 $ and $\lim_{n\rightarrow \infty} \Delta_n = 0.$ Furthermore, let $c, \epsilon, C$ and $q$ be positive constants such that $q>2,$ and let $K \geq 2$ be a fixed integer. Also, for any random vector $Z = (Z_1,...,Z_l)$, let $\left\| Z \right\|_{q} = \max_{1\leq j \leq l}\left\| Z_l \right\|_{q},$ where
$\left \| Z_l \right\|_{q} = \left( E\left[ \left| Z_l \right|^q \right] \right)^{\frac{1}{q}}$.
In order to ease notation, we assume that $n/K$ is an integer. For the sake of brevity we omit the dependence of probability $\Pr_P,$ expectation $E_P(\cdot),$ and norm $\left\| \cdot \right\|_{P,q}$ on the probability measure $P.$
\newline
Assumption 4 (regularity conditions and quality of plug-in parameter estimates): \newline
For all probability laws $P \in \mathcal{P}$
the following conditions hold for the random vector $( Y_2 ,D_1,D_2,X_0,X_1)$ for all $d_1,d_2 \in \{0,1,...,Q\}$:
enumerate• $ \left\| Y_2 \right\|_{q} \leq C,$
$\left\|E[Y_2^2| D_1 = d_1, D_2 = d_2, \underline{X}_1 ] \right\|_{\infty} \leq C^2$,
•
$\Pr(\epsilon \leq p_0^{d_1} (X_0) \leq 1-\epsilon) = 1,$
$\Pr(\epsilon \leq p_0^{d_2} (d_1,\underline{X}_1) \leq 1-\epsilon) = 1,$
•
$\left\| Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) \right\|_{2} = E_{ } \Big[\left(Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) \right)^2 \Big]^{\frac{1}{2}} \geq c$
• Given a random subset $I$ of $[n]$ of size $n_k=n/K,$ the nuisance parameter estimator $\hat \eta_0 = \hat \eta_0((W_i)_{i \in I^C})$ satisfies the following conditions. With $P$-probability no less than $1-\Delta_n:$
\begin{eqnarray}
\left\| \hat \eta_0 - \eta_0 \right\|_{q} &\leq& C, \notag \\
\left\| \hat \eta_0 - \eta_0 \right\|_{2} &\leq& \delta_n, \notag \\
\left\| \hat p_0^{d_1}(X_0)-1/2\right\|_{\infty} &\leq& 1/2-\epsilon, \notag\\
\left\| \hat p_0^{d_2}(D_1,X_1)-1/2\right\|_{\infty} &\leq & 1/2-\epsilon, \notag \\
\left\| \hat \mu_0^{Y_2}(D_2,X_1)-\mu^{Y_2}_0(D_2,X_1)\right\|_{2} \times \left\| \hat p_0^{d_1}(X_0)-p^{d_1}_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}, \notag \\
\left\| \hat \mu_0^{Y_2}(D_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{D}_2,\underline{X}_1)\right\|_{2} \times \left\| \hat p_0^{d_2}(D_1,\underline{X}_1)-p^{d_2}_0(D_1,\underline{X}_1)\right\|_{2} &\leq & \delta^_n n^{-1/2},\notag \\
\left\| \hat \nu_0^{Y_2}(\underline{D}_2,X_0)-\nu^{Y_2}_0(\underline{D}_2,X_0)\right\|_{2} \times \left\| \hat p_0^{d_1}(X_0)-p^{d_1}_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}.\notag
\end{eqnarray}
The only non-primitive condition is the condition (d). It puts restrictions on the quality of the nuisance parameter estimators. Condition (a) states that the distribution of the outcome does not have unbounded moments. (b) refines the common support condition such that the propensity scores are bounded away from $0$and $1$. Finally, (c) states that the covariates $\underline{X}_1$ do not perfectly predict the conditional mean outcome.
For demonstrating the $\sqrt{n}$-consistency of our estimator of the mean potential outcome, we show that it satisfies the requirements of the DML framework in Chetal2018 by first verifying linearity and Neyman orthogonality of the score (see Appendix (ref)). Then, as $ \psi^{\underline{d}_2}(W, \eta, \Psi^{\underline{d}_2}_{0}) $ is smooth in $ (\eta, \Psi^{\underline{d}_2}_{0}) $, it is sufficient that the plug-in estimators converge with a rate at least as fast as $ n^{-1/4} $ for achieving $n^{-1/2} $-convergence for the estimation of $ \hat{ \Psi}^{\underline{d}_2}$ as postulated in Theorem 1. This convergence rate of $ n^{-1/4} $ has been shown to be achieved by many commonly used machine learners under specific conditions, such as lasso, random forests, boosting and neural nets, see for instance Bellonietal2014, LuoSpindler2016, WagerAthey2018, and FarrellLiangMisra2018.\newline
Theorem 1\\
Under Assumptions 1-4, it holds for estimating $E[Y(\underline{d}_2)]$ based on Algorithm 1: \\
$\sqrt{n} \Big(\hat \Psi^{\underline{d}_2} - \Psi^{\underline{d}_2}_{0} \Big) \rightarrow N(0,\sigma_{\psi^{\underline{d}_2}})$, where $\sigma_{\psi^{\underline{d}_2}}= E[(\psi^{\underline{d}_2}-\Psi^{\underline{d}_2}_{0})^2]$. \\
The proof of Theorem 1 is provided in Appendix (ref).
\newline
Evaluation of weighted dynamic treatment effects
LechnerMiquel2010 show that under our assumptions, one may identify treatment effects for specific subgroups that are defined as a function of the distribution of the baseline covariates $X_0$. To this end, let $S$ denote a binary indicator for belonging to the subgroup of interest that satisfies $S \bot Y_2(\underline{d}_2)|X_0$, as $S$ may be selective in $X_0$, but not w.r.t.\ the post-treatment covariates $X_1$ after controlling for $X_0$. Furthermore, denote by $g(X_0)=\Pr(S=1|X_0)$ the probability of being in that group conditional on $X_0$. Interesting examples for such subgroups are the treated or non-treated populations in the first period, obtained by defining $S=I\{ D_1 = d_1\}$ with $d_1$ $\in$ $\{0,1,...,Q\}$. Mean potential outcomes conditional on $S=1$ are identified based on reweighting by $g(X_0)$, see e.g.\ Hirano+00 who use this approach for weighted ATE evaluation based on IPW. That is,
eqnarray[eqnarray omitted — 266 chars of source]
where the first equality follows from basic probability theory and the remaining ones from the fact that $S \bot Y_2(\underline{d}_2)|X_0$ and the law of iterated expectations. This suggests the following identification approach:
eqnarray[eqnarray omitted — 542 chars of source]
Note that the term $\frac{S}{\Pr(S=1)}\cdot \nu^{Y_2}(\underline{d}_2,X_0)$ in (ref) corresponds to $\frac{S}{\Pr(S=1)}\cdot E[Y_2(\underline{d}_2)|X_0]$ in (ref). Appendix (ref) shows that the moment condition $E[\psi^{\underline{d}_2,S=1}-E[Y_2(\underline{d}_2)|S=1]]=0$ holds, such that $E[\psi^{\underline{d}_2,S=1}]$ identifies the weighted mean potential outcome, and proves Neyman orthogonality. It demonstrates that DML is $\sqrt{n}$-consistent and asymptotically normal under Assumption 5 below. The latter formalizes the rate restrictions on the plug-in estimates, which now also contain an estimate of $g(X_0)$ denoted by $\hat{g}(X_0)$. To this end, Algorithm 1 outlined in Section (ref) is applied to estimate $E[Y_2(\underline{d}_2)|S=1]$ by using modified moment conditions in steps 3 and 4.
More specifically, the previously used $\hat \psi^{\underline{d}_2}_{i,k}$ computed in some subsample $k$ is replaced by
eqnarray[eqnarray omitted — 496 chars of source]
In step 4, the estimated scores $\hat \psi^{\underline{d}_2,S=1}_{i,k}$ are averaged over all observations across all $ K $ subsamples and divided by an estimate of $\Pr(S=1)$ to obtain an estimate of $\Psi^{\underline{d}_2,S=1}_0=E[Y_2(\underline{d}_2)|S=1]$ based on $\hat \Psi^{\underline{d}_2,S=1}=\Big[\sum_{k=1}^{K} \sum_{i=1}^{n_k} \hat \psi^{\underline{d}_2}_{i,k}\Big]\Big/\Big[\sum_{k=1}^{K} \sum_{i=1}^{n_k}S_i\Big]$.
The following assumption refines the conditions of Assumption 4 such that asymptotic normality holds for the DML estimator based on ((ref)).\newline
Assumption 5 (regularity conditions and quality of plug-in parameter estimates): \newline
For all probability laws $P \in \mathcal{P}$
the following conditions hold for the random vector $( Y_2 ,D_1,D_2,X_0,X_1, S)$ for all $d_1,d_2 \in \{0,1,...,Q\}$:
enumerate• $ \left\| Y_2 \right\|_{q} \leq C,$
$\left\|E[Y_2^2| D_1 = d_1, D_2 = d_2, \underline{X}_1 ] \right\|_{\infty} \leq C^2$,
•
$\Pr(\epsilon \leq p_0^{d_1} (X_0) \leq 1-\epsilon) = 1$
$\Pr(\epsilon \leq p_0^{d_2} (d_1,\underline{X}_1) \leq 1-\epsilon) = 1$
•
$\left\| Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) \right\|_{2} = E_{ } \Big[\left(Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) \right)^2 \Big]^{\frac{1}{2}} \geq c$
• Given a random subset $I$ of $[n]$ of size $n_k=N/K,$ the nuisance parameter estimator $\hat \chi_0 = \hat \chi_0((W_i)_{i \in I^C})$ satisfies the following conditions. With $P$-probability no less than $1-\Delta_n:$
\begin{eqnarray}
\left\| \hat \chi_0 - \chi_0 \right\|_{q} &\leq& C, \notag \\
\left\| \hat \chi_0 - \chi_0 \right\|_{2} &\leq& \delta_n, \notag \\
\left\| \hat g(X_0)-1/2\right\|_{\infty} &\leq& 1/2-\epsilon, \notag\\
\left\| \hat p_0^{d_1}(X_0)-1/2\right\|_{\infty} &\leq& 1/2-\epsilon, \notag\\
\left\| \hat p_0^{d_2}(D_1,X_1)-1/2\right\|_{\infty} &\leq & 1/2-\epsilon, \notag \\
\left\| \hat \chi_0^{Y_2}(D_2,X_1)-\mu^{Y_2}_0(D_2,X_1)\right\|_{2} \times \left\| \hat p_0^{d_1}(X_0)-p^{d_1}_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}, \notag \\
\left\| \hat \mu_0^{Y_2}(D_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{D}_2,\underline{X}_1)\right\|_{2} \times \left\| \hat p_0^{d_2}(D_1,\underline{X}_1)-p^{d_2}_0(D_1,\underline{X}_1)\right\|_{2} &\leq & \delta^_n n^{-1/2},\notag \\
\left\| \hat \nu_0^{Y_2}(\underline{D}_2,X_0)-\nu^{Y_2}_0(\underline{D}_2,X_0)\right\|_{2} \times \left\| \hat p_0^{d_1}(X_0)-p^{d_1}_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}.\notag \\
\left\| \hat\mu^{Y_2}(\underline{D}_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{D}_2,\underline{X}_1)\right\|_{2} \times \left\| \hat g(X_0)-g_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}, \notag \\
\left\| \hat \nu^{Y_2}(\underline{D}_2,X_0)-\nu^{Y_2}_0(\underline{D}_2,X_0)\right\|_{2} \times \left\| \hat g(X_0)-g_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}.\notag
\end{eqnarray}
Assumption 5 can be satisfied if the plug-in estimator $\hat g(X_0)$ converges to its' true value $g_0(X_0)$ with rate $ n^{-1/4}$ just like the estimators of the other nuisance terms. Then, the average treatment effect in the subgroup, denoted by
eqnarray[eqnarray omitted — 114 chars of source]
is $\sqrt{n}$-consistently estimated, as postulated in Theorem 2.\newline
Theorem 2\\
Under Assumptions 1-3 and 5, it holds for estimating $E[Y_2(\underline{d}_2)|S=1]$ based on Algorithm 1: \\
$\sqrt{n} \Big(\hat \Psi^{\underline{d}_2,S=1} - \Psi^{\underline{d}_2,S=1}_{0} \Big) \rightarrow N(0,\sigma_{\psi^{\underline{d}_2,S=1}})$, where $\sigma_{\psi^{\underline{d}_2,S=1}}= E[(\psi^{\underline{d}_2,S=1}-\Psi^{\underline{d}_2,S=1}_{0})^2]$. \\
The proof of Theorem 2 is provided in Appendix (ref).
Simulation study
This section provides a simulation study to investigate the finite sample behavior of our double machine learning method for dynamic treatment effects based on the following data generating process:
eqnarray*[eqnarray* omitted — 313 chars of source]
Outcome $Y_2$ is a function of the observed variables $D_1,D_2,X_0,X_1,$ and the unobserved scalar $U$.
The treatment effects of both $D_1$ and $D_2$ are equal to 1. $D_1$ is a function of $X_0$ and the unobserved scalar $V$. $D_2$ is a function of both pre- and post-treatment covariates $X_0$ and $X_1$, the first treatment $D_1$, and the unobservable scalar $W$. Both $X_0$ and $X_1$ are vectors of covariates of dimension $p$, drawn from a multivariate normal distribution with zero mean and covariance matrices $\Sigma_0$ and $\Sigma_1$, respectively. $U, V, W$ are random and standard normally distributed. We consider two sample sizes of $n=2500$ and $10000$, running $1000$ simulations for the smaller and $250$ simulations for the larger sample sizes.
In our simulations, we set $p$, the number of covariates in $X_1$ and $X_0$, respectively, to 50 or 100. $\Sigma_0$ and $\Sigma_1$ are defined based on setting the covariance of the $i$th and $j$th covariate in $X_0$ or $X_1$ to $0.5^{|i-j|}$.
The coefficients $\beta_{X_0}$ and $\beta_{X_1}$ gauge the impacts of the covariates on $Y_2$, $D_2$, and $D_1$, respectively, and thus, the magnitude of confounding. The $i$th element in the coefficient vectors $\beta_{X_0}$ and $\beta_{X_1}$ is set to $0.4/i^4$ for $i=1,...,p$, implying a quadratic decay of covariate importance in terms of confounding.
As reported in Table (ref), this specification implies that the $R^2$ statistic based on linearly predicting $Y_2$ by $\underline{X}_1$ ranges from 36 to 41%, depending on the number of covariates and the sample size. Furthermore, the Nagelkerke1991 pseudo-$R^2$ when predicting $D_1$ by $X_0$ and $D_2$ by $D_1,\underline{X}_1$ based on probit models ranges from 13 to 17% and 26 to 33%, respectively. These figures point to a substantial level of confounding as it may be reasonably encountered in empirical applications.
table[table omitted — 598 chars of source]
We investigate the performance of ATE estimation when comparing the sequences of obtaining both treatments $(\underline{d}_2=(d_1=1,d_2=1))$ vs.\ no treatment $(\underline{d}^*_2=(d_1=0,d_2=0))$ in the total population based on Theorem 1 and in the treated in the first period based on Theorem 2. The nuisance parameters, i.e.\ the linear and probit specifications of the outcome and treatment equations, are estimated by lasso regressions using the default options of the SuperLearner package provided by vanderLaanetal2007 for the statistical software R. 3-fold cross-fitting is used for the estimation of the treatment effects. We drop observations whose products of estimated treatment propensity scores in the first and second period, $\hat{p}^{d_1}(X_0)\cdot \hat{p}^{d_2}(D_1,\underline{X}_1)$, are close to zero, namely smaller than a trimming threshold of $0.01$ (or 1%). This avoids an explosion of the propensity score-based weights and thus of the variance when estimating the mean potential outcomes by the sample analogue of identification result (ref), where the product of the propensity scores enters the denominator for reweighing the outcome. Our estimation procedure is available in the causalweight package for R by BodoryHuber2018.
table[table omitted — 1,405 chars of source]
Table (ref) presents the main findings when estimating the ATE in the total population, $\hat{\Delta}(\underline{d}_2,\underline{d}^*_2)$, and among the subgroup of treated in the first period, $\hat{\Delta}(\underline{d}_2,\underline{d}^*_2,S=1)$. Irrespective of the number of covariates, the absolute biases go to zero as the sample size increases. Furthermore, the standard deviations and root mean squared errors (RMSE) of the ATE estimators are roughly cut by half when quadrupling the sample size, as implied by $\sqrt{n}$-consistency. The levels of the standard deviations and RMSEs are somewhat higher for $\hat{\Delta}(\underline{d}_2,\underline{d}^*_2,S=1)$ than for $\hat{\Delta}(\underline{d}_2,\underline{d}^*_2)$, which comes from the additional weighting step due to targeting the treated subpopulation with $S=1$. We also observe that the average standard errors (average SE) based on the asymptotic variance approximations appear to converge at $\sqrt{n}$-rate, however, they underestimate the true standard deviations. This results in under-coverage of the true effects when constructing 95% confidence intervals based on those standard errors, an issue that decreases in the sample size.
Empirical application
We apply our double machine learning approach to evaluate the effects of training sequences provided by the Job Corps program on employment. Job Corps is the largest U.S.\ program offering vocational training and academic classroom instruction for disadvantaged individuals aged 16 to 24. It is financed by the U.S.\ Department of Labor and currently has about 50,000 participants every year.
Besides vocational credentials, students may obtain a high school diploma or equivalent qualifications. Individuals meeting specific low-income requirements can participate in Jobs Corps without any costs.
A range of studies analyzes the impact of Job Corps based on an experimental study with randomized access to the program between November 1994 and February 1996. In particular, ScBuGl01 and ScBuMc2008 discuss in detail the study design and report the average effects of random program assignment on a broad range of outcomes. Their findings suggest that Job Corps increases educational attainment, reduces criminal activity, and increases employment and earnings, at least for some years after the program. Floresetal2012 assess the impact of a continuously defined treatment, namely the length of exposure to academic and vocational instruction on earnings and find positive effects. As the length of the treatment is (in contrast to program assignment) not random, they impose a conditional independence assumption and control for baseline characteristics at Job Corps assignment. ColangeloLee2020 suggest double machine learning-based estimation of continuous treatment effects and apply it to assess the employment effects of Job Corps. In contrast to these contributions on continuous treatment doses of Job Corps, we consider discrete sequences of multiple treatments and also control for post-treatment confounders rather than baseline covariates only.
Several contributions assess specific causal mechanisms of the program. FlFl09 find a positive direct effect of program assignment on earnings when controlling for work experience which they assume to be conditionally independent given observed covariates. Also Huber2012 imposes a conditional independence assumption and estimates a positive direct health effect when controlling for the mediator employment. Using a partial identification approach permitting mediator endogeneity, FlFl10 compute bounds on the direct and indirect effects of Job Corps assignment on employment and earnings mediated by obtaining a GED, high school degree, or vocational degree. Under their strongest set of assumptions, the results point to a positive direct effect net of obtaining a degree. FrHu17 use an instrumental variable strategy based on two instruments to disentangle the earnings effect of being enrolled in Job Corps into an indirect effect via hours worked and a direct effect, likely related to a change in human capital. Their results point to the existence of an indirect rather than a direct mechanism. Even though our framework of analyzing sequences of treatments is in terms of statistical issues somewhat related to the evaluation of causal mechanisms, it relies on distinct identifying assumptions than the previously mentioned studies, which e.g.\ do not consider controlling for post-treatment confounders.
Our sample consists of 11313 individuals with completed follow-up interviews four years after randomization, out of which 6828 and 4485 were randomized in and out of Job Corps, respectively. We exploit the sequential structure of academic education and vocational training in the program to define dynamic treatment states. Since most of the education and training activities were taken in the first two years, we focus on the latter when generating a sequence of binary treatments for each observation.
The treatment states in our application can take four different values: $d_1$,$d_2$,$d_1^*$,$d_2^*$ $\in \{0,1,2,3\}$. State 0 refers to no instruction offered due to being randomized out of Job Corps (control group), 1 to no instruction despite being randomized in (never takers in the denomination of Angrist+96), 2 to academic education among program participants, and 3 to vocational training among program participants. If individuals participate in both academic education and vocational training in a specific year, we assign the code of the treatment that was attended to a larger extent in terms of completed hours.
table[table omitted — 1,133 chars of source]
Table (ref) reports various sequences of treatments in the data along with the corresponding number of observations. For instance, the treatment sequence 00 refers to those 4485 control group members that were randomized out and did not participate in any education activities offered by Job Corps. Furthermore, 320 individuals assigned to Job Corps do not participate in any form of education either, as indicated by the sequence 11. We also note that for 2610 out of the 11313 individuals, information on the treatment sequences is missing. The literature explains the missing values by a random skip logic error, due to which asking questions about treatment participation was randomly omitted for a subset of survey participants, see page J.5 in ScEtAl2003. In our analysis, we drop the control group with treatment sequence 00, but make use of it in a placebo test outlined further below. Furthermore, for several potential comparisons of treatment sequences, small sample issues and/or problems of a lack of common support in propensity scores (and thus, covariates) arise. For this reason, we confine our evaluation to comparing treatment sequence 33 (vocational training in both years) to either 22 (academic education in both years), 21 (academic education in the first year), or 11 (no participation in either year).
table[table omitted — 737 chars of source]
Our outcome variable is a binary employment indicator measured four years after randomization. Table (ref) reports the mean outcome across various treatment sequences, which ranges from 77 to 89 percent. It also provides the sequence-specific numbers of cases with missing outcomes that are dropped from the analysis, which appear quite low. We aim at estimating the ATE of treatment sequences $\underline{d}_2$ vs.\ $\underline{d}^*_2$ among individuals whose treatment in the first year corresponds to the first-year-treatment of either $\underline{d}_2$ or $\underline{d}^*_2$. An alternative would be to assess the ATE in the total sample randomized into Job Corps (which would thus also include individuals with different first-year treatments than the ones evaluated), but this proved to be problematic due to lacking common support in terms of treatment propensity scores.
We make use of a large set of potential control variables that also include covariates which have been identified as important confounders in several articles assessing the sensitivity of program evaluations to the inclusion and omission of such confounders in observational labor market studies. BiFiOsPa14, for instance, conclude that imposing conditional independence assumptions requires the availability of rich data on employment and benefit histories, and socio-economic characteristics. LeWu13 point to the importance of factors like health, caseworker assessments, regional information, timing of unemployment and program start, pre-treatment outcomes, job search behavior, and labor market histories. In line with these findings, our covariates comprise information about socio-economic characteristics, pre-treatment labor market histories, education and training, job search activities, welfare receipt, health, crime, and how one learnt about the existence of Job Corps. Table (ref) in the Appendix (ref) reports more details on these features, including variable descriptions and distributions across treatment sequences.
We condition on observed characteristics $X_t$ in periods $t \in \{0,1\}$. $X_0$ denotes control variables measured at baseline prior to the first treatment $D_1$, whereas $X_1$ is observed one year after randomization but prior to the second treatment $D_2$. Table (ref) provides the number and types of variables assigned to $X_0$ and $X_1$. Our raw data include 1188 characteristics. After some data manipulations based on generating dummies for values of categorical variables and missing items in dummy or categorical variables, we end up with all in all 2336 regressors. Missing observations in numerical variables were replaced by the mean values of the non-missing items. Furthermore, we standardized numerical covariates to have a zero mean and a standard deviation of 0.5.
table[table omitted — 619 chars of source]
We estimate $\Delta(\underline{d}_2,\underline{d}^*_2, S=1)$, with $S=1$ if the first treatment corresponds to either the first treatment in $\underline{d}_2$ or $\underline{d}^*_2$, based on 3-fold cross-fitting and the random forest (see Breiman2001) as machine learner of the nuisance parameters. To this end, we use the SuperLearner package with default options provided by vanderLaanetal2007 for the statistical software R. Our motivation for choosing the random forest is that it is (in the spirit of kernel regression) a nonparametric estimator that does not impose functional form assumptions (like linearity) on the conditional outcome or treatment models. As in our simulation study, we drop observations whose products of propensity scores in the first and second period are smaller than $0.01$ to impose common support in our sample
and avoid an explosion in the propensity score-based weights.
For a visual assessment of the common support, Appendix (ref) provides plots with the propensity score distributions across all treatment sequences considered in this application. In general, common support is rather decent for the first period propensity scores $\hat{p}^{d_1}(X_0)$, while the overlap is weaker for the scores in the second period $\hat{p}^{d_2}(D_1,\underline{X}_1)$, especially at the boundaries of the distributions.
table[table omitted — 1,270 chars of source]
Table (ref) presents the results for our three different comparisons of treatment sequences. As displayed in the first and second rows, we find no statistically significant increase in employment when attending two years of vocational training rather than one or two years of academic classroom training, respectively. Even though the point estimate $\hat{\Delta}(\underline{d}_2,\underline{d}^*_2, S=1)$ suggests an increase of 8 and 4 percentage points in the employment probability (starting from a counterfactual probability of 77% and 82%, respectively), the p-values are beyond any conventional level of statistical significance. For the comparison of vocational training to no training in either year presented in the third row, however, the effect of 8 percentage points is statistically significant at the 5% level. We therefore conclude that vocational training appears to increase the employment probability 4 years after randomization into Job Corps, while it is less clear whether it performs relatively better than academic classroom training. The results are qualitatively similar when increasing the trimming threshold for the products of the propensity scores to $0.03$, see Table (ref). However, the p-value of the effect of vocational vs.\ no training is now somewhat higher (6%), while the effect of vocational training (in both periods) vs.\ classroom training in the first period only is borderline significant at the 10% level.
table[table omitted — 1,297 chars of source]
To partially assess the validity of the conditional independence assumptions imposed in this application, we conduct a placebo test based on comparing the outcomes of two control groups as for instance discussed in AthImb17. The first control group are the never takers, i.e.\ those randomized into Job Corps who never attended any form of instruction with treatment sequence 11. The second control group are those randomized out and thus without access to Job Corps instruction with treatment sequence 00. We estimate the pseudo-treatment effect of Job Corps on the employment outcome using the double machine learning approach for assessing static (rather than dynamic) treatments as for instance discussed in Chetal2018. To this end, we consider sequence 11 as pseudo-treatment and sequence 00 as non-treatment and control for the baseline covariates $X_0$ based on the random forest as machine learner of the nuisance parameters. As neither group attended any training, the true ATE is equal to zero. As shown in Table (ref), the estimated ATE is indeed approximately zero with a p-value of 93%. This provides some statistical support for the satisfaction of the conditional independence assumption, at least w.r.t.\ the baseline covariates $X_0$.
table[table omitted — 693 chars of source]
Conclusion
In this paper, we combined dynamic treatment evaluation with double machine learning under sequential selection-on-observables assumptions which avoids adhoc pre-selection of control variables. This approach appears particularly fruitful in high-dimensional data with many potential control variables. We suggested estimators for the (weighted) average effects of sequences of treatments (with the so-called controlled direct effect being a special case) based on Neyman orthogonal score functions, sample splitting, and machine learning-based plug-in estimates of conditional mean outcomes and treatment propensity scores. We demonstrated the $\sqrt{n}$-consistency and asymptotic normality of the treatment effect estimators under specific regularity conditions and analyzed their finite sample behavior in a Monte Carlo simulation. Finally, we applied our method to the Job Corps data to analyze the effects of distinct sequences of educational programs and found positive employment effects for vocational training when compared to no program participation.
appendix\numberwithin{equation}{section}
Appendices
{
\section{Proofs}
\subsection{Proof of Theorem 1}
For the proof of Theorem 1 it is sufficient to check the conditions of Assumptions 3.1 and 3.2 from Theorem 3.1 and 3.2 and Corollary 3.2 from Chetal2018. All bounds hold uniformly over $P \in \mathcal{P},$ where $\mathcal{P}$ is the set of all possible probability laws, and we omit $P$ for brevity.
Define the nuisance parameters to be the vector of functions $\eta=(p^{d_1}(X_0), p^{d_2}(D_1,\underline{X}_1), \mu^{Y_2}(\underline{D}_2,\underline{X}_1))$,
$ \nu^{Y_2}(D_1,X_0)$, with $p^{d_1}(X_0)=\Pr(D_1=d_1|X_0)$, $p^{d_2}(D_1,\underline{X}_1)=\Pr(D_2=d_2|D_1,X_0, X_1)$, $\mu^{Y_2}(\underline{D}_2,\underline{X}_1)=E[Y_2|\underline{D}_2,X_0,X_1]$, and $\nu^{Y_2}(\underline{D}_2,X_0)=\int E[Y_2|\underline{d}_2,X_0,X_1=x_1] dF_{X_1=x_1|D_1,X_0}$, where $F_{X_1=x_1|D_1,X_0}$ denotes the conditional distribution function of $X_1$ at value $x_1$. The score function for the counterfactual $\Psi^{\underline{d}_2}_{0}=E[Y_2(\underline{d}_2)]$ is given by:
\begin{eqnarray}
\psi^{d_2}(W, \eta, \Psi^{d_2}_{0}) &=& \frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu^{Y_2}(d_2,X_1)]}{p^{d_1}(X_0)\cdot p^{d_2}(d_1,X_1)} \notag\\
& + & \frac{I\{D_1=d_1\}\cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu^{Y_2}(\underline{d}_2,X_0)]}{p^{d_1}(X_0)} \notag\\
& + &\nu^{Y_2}(\underline{d}_2,X_0) - \Psi^{\underline{d}_2}_{0}. \notag
\end{eqnarray}
Let $\mathcal{T}_n$ be the set fo all $\eta=(p^{d_1}, p^{d_2},\mu^{Y_2}, \nu^{Y_2})$ consisting of $P$-square integrable functions $p^{d_1}, p^{d_2},\mu^{Y_2}$ and $\nu^{Y_2}$ such that
\begin{eqnarray}
\left\| \eta - \eta_0 \right\|_{q} &\leq& C, \\
\left\| \eta - \eta_0 \right\|_{2} &\leq& \delta_n, \notag \\
\left\| p^{d_1}(X_0)-1/2\right\|_{\infty} &\leq& 1/2-\epsilon, \notag\\
\left\| p^{d_2}(D_1,\underline{X}_1)-1/2)\right\|_{\infty} &\leq & 1/2-\epsilon, \notag \\
\left\| \mu^{Y_2}(\underline{D}_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{D}_2,\underline{X}_1)\right\|_{2} \times \left\| p^{d_1}(X_0)-p^{d_1}_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}, \notag \\
\left\| \mu^{Y_2}(\underline{D}_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{D}_2,\underline{X}_1)\right\|_{2} \times \left\| p^{d_2}(D_1,\underline{X}_1)-p^{d_2}_0(D_1,\underline{X}_1)\right\|_{2} &\leq & \delta^_n n^{-1/2},\notag \\
\left\| \nu^{Y_2}(\underline{D}_2,X_0)-\nu^{Y_2}_0(\underline{D}_2,X_0)\right\|_{2} \times \left\| p^{d_1}(X_0)-p^{d_1}_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}.\notag
\end{eqnarray}
We furthermore replace the sequence $(\delta_n)_{n \geq 1}$ by $(\delta_n')_{n \geq 1},$ where $\delta_n' = C_{\epsilon} \max(\delta_n,n^{-1/2}),$ where $C_{\epsilon}$ is sufficiently large constant that only depends on $C$ and $\epsilon.$
\textbf{Assumption 3.1: Linear scores and Neyman orthogonality}
\newline
\textbf{Assumption 3.1(a)}
\textbf{Moment Condition:} The moment condition $E\Big[\psi^{\underline{d}_2}(W, \eta_0, \Psi^{\underline{d}_2}_{0})\Big] = 0$ is satisfied, which follows from the law of iterated expectations:
\begin{eqnarray}
E\Big[\psi^{\underline{d}_2}(W, \eta_0, \Psi^{\underline{d}_2}_{0})\Big] &=& E\Bigg[\overbrace{ E\Bigg[\frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} }{p^{d_1}_0(X_0)\cdot p^{d_2}_0(d_1,\underline{X}_1)} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]\Bigg|X_0\Bigg]}^{=E[E[Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)|\underline{D}_2=\underline{d}_2,\underline{X}_1]|D_1=d_1,X_0]=0} \Bigg] \notag\\
&+& \ E\Bigg[\overbrace{ E\Bigg[ \frac{I\{D_1=d_1\}\cdot [ \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}{p_0^{d_1}(X_0)} \Bigg| X_0 \Bigg]}^{=\int E\big[ \mu_0^{Y_2}(\underline{d}_2,\underline{x}_1)-\nu_0^{Y_2}(\underline{d}_2,x_0) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0}=0} \Bigg] \notag\\
&+& \ E\big[ \nu_0^{Y_2}(\underline{d}_2,X_0) \big] \ \ - \ \ \Psi^{\underline{d}_2}_{0} \ \ = \ \ \Psi^{\underline{d}_2}_{0}\ \ - \ \ \Psi^{\underline{d}_2}_{0} \ \ = 0 \notag
\end{eqnarray}
To better see this result, note that
\begin{eqnarray}
&&E\Bigg[\frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} }{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \cdot [Y_2- \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]\Bigg|X_0\Bigg]\notag\\
&=&E\Bigg[\frac{I\{D_2=d_2\} }{ p_0^{d_2}(d_1,\underline{X}_1)} \cdot [Y_2- \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]\Bigg|D_1=d_1,X_0\Bigg]\notag\\
&=&E\Bigg[ E\Bigg[\frac{I\{D_2=d_2\} }{ p_0^{d_2}(d_1,\underline{X}_1)} \cdot [Y_2- \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]\Bigg|D_1=d_1,\underline{X}_1)\Bigg] \Bigg|D_1=d_1,X_0\Bigg]\notag\\
&=&E [ E[Y_2- \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) |\underline{D}_2=\underline{d}_2,\underline{X}_1 ] |D_1=d_1,X_0 ]\notag \\
&=&E [ \mu^{Y_2}_0(\underline{d}_2,\underline{X}_1) - \mu^{Y_2}_0(\underline{d}_2,\underline{X}_1)|D_1=d_1,X_0 ]=0, \notag
\end{eqnarray}
where the first and third equalities follow from basic probability theory and the second from the law of iterated expectations.
Furthermore,
\begin{eqnarray}
&&E\Bigg[ \frac{I\{D_1=d_1\} \cdot [ \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)- \nu_0^{Y_2}(\underline{d}_2,x_0)]}{p^{d_1}_0(x_0)} \Bigg| X_0 = x_0 \Bigg]\notag\\
&=&E\big[ \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)- \nu_0^{Y_2}(\underline{d}_2,x_0) \big| D_1=d_1, X_0 = x_0 \big]\notag\\
&=& \int E\big[ \mu_0^{Y_2}(\underline{d}_2,\underline{x}_1)- \nu_0^{Y_2}(\underline{d}_2,x_0) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0=x_0}\notag\\
&=& \int E\big[ \mu_0^{Y_2}(\underline{d}_2,\underline{x}_1) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0=x_0}-\nu_0^{Y_2}(\underline{d}_2,x_0)\notag\\
&=& \nu^{Y_2}_0(\underline{d}_2,x_0)-\nu^{Y_2}_0(\underline{d}_2,x_0) =0.\notag
\end{eqnarray}
where the first equality follows from basic probability theory, the second from conditioning on and integrating over $X_1$, and the third from the fact that $ \nu_0^{Y_2}(\underline{d}_2,X_0)$ is not a function of $X_1$.
\textbf{Assumption 3.1(b)}
\textbf{Linearity:} The score $ \psi^{\underline{d}_2}(W, \eta_0, \Psi^{\underline{d}_2}_{0}) $ is linear in $\Psi^{\underline{d}_2}_{0}$ :
$\psi^{\underline{d}_2}(W, \eta_0, \Psi^{\underline{d}_2}_{0}) = \psi^{\underline{d}_2}_a(W, \eta_0) \cdot\Psi^{\underline{d}_2}_0 + \psi^{\underline{d}_2}_b(W, \eta_0) $
with $\psi^{\underline{d}_2}_a(W, \eta_0) = -1$ and
\begin{eqnarray}
\psi^{\underline{d}_2}_b(W, \eta_0) &=&\frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)}\notag\\
& + & \frac{I\{D_1=d_1\}\cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu^{Y_2}(\underline{d}_2,X_0)]}{p^{d_1}(X_0)} + \nu^{Y_2}(\underline{d}_2,X_0). \notag
\end{eqnarray}
\textbf{Assumption 3.1(c)}
\textbf{Continuity:}
The expression for the second Gateaux derivative of a map $\eta \mapsto E[\psi^{\underline{d}_2}(W, \eta, \Psi^{\underline{d}_2})]$ is continuous.
\textbf{Assumption 3.1(d)}
\textbf{Neyman Orthogonality}: For any $\eta \in \mathcal{T}_N,$ the Gateaux derivative in the direction $ \eta - \eta_0 =
(p^{d_1}(X_0)-p_0^{d_1}(X_0), p^{d_2}(D_1,\underline{X}_1)-p_0^{d_2}(D_1,\underline{X}_1),\mu^{Y_2}(\underline{d}_2,X_0)-\mu_0^{Y_2}(\underline{d}_2,X_0), \nu^{Y_2}(\underline{d}_2,X_0)-\nu_0^{Y_2}(\underline{d}_2,X_0)) $ is given by:
\begin{align}
&\partial E \big[\psi^{\underline{d}_2}(W, \eta, \Psi^{\underline{d}_2})\big] \big[\eta - \eta_0 \big] = \notag\\
& - E \Bigg[ \frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \Bigg] \tag{$*$}\\
& + E \Bigg[ \frac{I\{D_1=d_1\} \cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)} \Bigg] \tag{$**$}\\
&- \ E \Bigg[ \frac{\overbrace{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}^{E[\cdot|X_0]=E[E[Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)|\underline{D}_2=\underline{d}_2,\underline{X}_1]|D_1=d_1,X_0]=0}}{ p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1) }\cdot\frac{[p^{d_1}(X_0)-p_0^{d_1}(X_0)] }{p_0^{d_1}(X_0)} \Bigg] \notag\\
& - \ E \Bigg[ \overbrace{\frac{I\{D_1=d_1\}\cdot [\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}{p_0^{d_1}(X_0)}}^{E[\cdot|X_0]=\int E\big[ \mu_0^{Y_2}(\underline{d}_2,\underline{x}_1)-\nu_0^{Y_2}(\underline{d}_2,x_0) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0}=0} \cdot \frac{[p^{d_1}(X_0)-p_0^{d_1}(X_0)] }{p_0^{d_1}(X_0)} \Bigg] \notag \\
&- \ E \Bigg[ \frac{\overbrace{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}^{E[\cdot|X_0]=E[E[Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)|\underline{D}_2=\underline{d}_2,\underline{X}_1]|D_1=d_1,X_0]=0}}{ p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1) }\cdot\frac{[p^{d_2}(d_1,\underline{X}_1)-p_0^{d_2}(d_1,\underline{X}_1)] }{p_0^{d_2}(d_1,\underline{X}_1)} \Bigg] \notag\\
&\underbrace{ - \ E \Bigg[ \underbrace{\frac{I\{D_1=d_1\} \cdot [\nu^{Y_2}(\underline{d}_2,X_0)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}{p_0^{d_1}(X_0)}}_{ E[\cdot|X_0]=\frac{p_0^{d_1}(X_0)}{p_0^{d_1}(X_0)}\cdot[\nu^{Y_2}(\underline{d}_2,X_0)-\nu_0^{Y_2}(\underline{d}_2,X_0)]} \Bigg]+ E[\nu^{Y_2}(\underline{d}_2,X_0)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}_{=0} =0\notag
\end{align}
The Gateaux derivative is zero because expressions $(*)$ and $(**)$ cancel out. To see this, note that
\begin{eqnarray}
&&E\Bigg[ \frac{I\{D_1=d_1\} \cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p^{d_1}(x_0)} \Bigg| X_0 = x_0 \Bigg]\notag\\
&=&E\big[ \mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) \big| D_1=d_1, X_0 = x_0 \big]\notag\\
&=& \int E\big[ \mu^{Y_2}(\underline{d}_2,\underline{x}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{x}_1) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0=x_0}, \notag
\end{eqnarray}
where the first equality follows from basic probability theory and the second from conditioning on and integrating over $X_1$. Furthermore,
\begin{eqnarray}
&&E\Bigg[ \frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p^{d_1}(x_0) \cdot p_0^{d_2}(d_1,\underline{X}_1) } \Bigg| X_0 = x_0 \Bigg]\notag\\
&=&E\Bigg[ \frac{I\{D_2=d_2\} \cdot[\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]} {p_0^{d_2}(d_1,\underline{X}_1) } \Bigg| D_1=d_1, X_0 = x_0 \Bigg]\notag\\
&=& \int E\Bigg[ \frac{I\{D_2=d_2\} \cdot [\mu^{Y_2}(\underline{d}_2,\underline{x}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_2}(d_1,\underline{x}_1) } \Bigg| D_1=d_1, \underline{x}_1=\underline{x}_1 \Bigg] dF_{X_1=x_1|D_1=d_1,X_0=x_0}\notag\\
&=& \int E\big[ \mu^{Y_2}(\underline{d}_2,\underline{x}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{x}_1) \big| D_1=d_1, D_2=d_2, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0=x_0}\notag\\
&=& \int E\big[ \mu^{Y_2}(\underline{d}_2,\underline{x}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{x}_1) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0=x_0},\notag
\end{eqnarray}
where the first equality follows from basic probability theory, the second from conditioning on and integrating over $X_1$, the third from basic probability theory, and the fourth from simplification as $\mu^{Y_2}(\underline{d}_2,\underline{x}_1)=E[Y_2|D_1=d_1,D_2=d_2,\underline{X}_1=\underline{x}_1]$ is already conditional on $D_2=d_2$.
\begin{align}
&\partial E \big[\psi^{\underline{d}_2}(W, \eta, \Psi^{\underline{d}_2})\big] \big[\eta - \eta_0 \big] = 0 \notag
\end{align}
proving that the score function is orthogonal.
\textbf{Assumption 3.1(e)}
\textbf{Singular values of $E[\psi^{\underline{d}_2}_a(W;\eta_0)]$ are bounded:}
Holds trivially, because $\psi^{\underline{d}_2}_a(W;\eta_0) = -1.$
\textbf{Assumption 3.2: Score regularity and quality of nuisance parameter estimators}
\textbf{Assumption 3.2(a)}
This assumption directly follows from the construction of the set $\mathcal{T}_n$ and the regularity conditions (Assumption 4).
\textbf{Assumption 3.2(b)}
\textbf{Bound for $m_n$:}
\begin{eqnarray}
\left\| \mu^{Y_2}_0(\underline{D}_2,\underline{X}_1) \right\|_{q} &=& \left( E\left[ \left| \mu_0^{Y_2}(\underline{D}_2,\underline{X}_1) \right|^q \right] \right)^{\frac{1}{q}} \notag \\
&=& \left( \sum_{\underline{d}_2 \in \{0,1,...,Q\}^2} E\left[ \left| \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) \right|^q \Pr _{P}(\underline{D}_2=\underline{d}_2|\underline{X}_1) \right] \right)^{\frac{1}{q}} \notag \\
&\geq& \epsilon^{2/q} \left( \sum_{\underline{d}_2 \in \{0,1,...,Q\}^2} E\left[ \left| \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) \right|^q \right] \right)^{\frac{1}{q}} \notag \\
&\geq& \epsilon^{2/q} \left( \max_{\underline{d}_2 \in \{0,1,...,Q\}^2} E\left[ \left| \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) \right|^q \right] \right)^{\frac{1}{q}} \notag \\
&=& \epsilon^{2/q} \left( \max_{\underline{d}_2 \in \{0,1,...,Q\}^2} \left\| \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1) \right\|_{q}\right), \notag
\end{eqnarray}
where the first equality follows from definition, the second from the law of total probability, and the third line from the fact that $\Pr(\underline{D}_2 = \underline{d}_2|\underline{X}_1) = p_0^{d_1} (X_0) \cdot p_0^{d_2} (d_1,\underline{X}_1) \geq \epsilon^2.$ Similarly, we obtain
\begin{equation}
\left\| \nu^{Y_2}_0(\underline{D}_2,X_0) \right\|_{q} \geq \epsilon^{2/q} \left( \max_{\underline{d}_2 \in \{0,1,...,Q\}^2} \left\| \nu_0^{Y_2}(\underline{d}_2,X_0) \right\|_{q}\right). \notag
\end{equation}
Notice that by Jensen's inequality $\left\| \mu^{Y_2}_0(\underline{D}_2,\underline{X}_1) \right\|_{q} \leq \left\| Y_2 \right\|_{q}$ and
$\left\| \nu^{Y_2}_0(\underline{D}_2,X_0) \right\|_{q} \leq \left\| Y_2 \right\|_{q}$ and hence
$\left\| \mu^{Y_2}_0(\underline{d}_2,\underline{X}_1) \right\|_{q} \leq C/\epsilon^{2/q}$ and
$\left\| \nu^{Y_2}_0(\underline{d}_2,X_0) \right\|_{q} \leq C/\epsilon^{2/q},$
by conditions ((ref)). Similarly, for any $\eta \in \mathcal{T}_N:$
$\left\| \mu^{Y_2}(\underline{d}_2,\underline{X}_1) - \mu^{Y_2}_0(\underline{d}_2,\underline{X}_1) \right\|_{q} \leq C/\epsilon^{2/q}$ and
$\left\| \nu^{Y_2}(\underline{d}_2,X_0) - \nu^{Y_2}_0(\underline{d}_2,X_0) \right\|_{q} \leq C/\epsilon^{2/q},$ because
$\left\| \mu^{Y_2}(\underline{D}_2,\underline{X}_1) - \mu^{Y_2}_0(\underline{D}_2,\underline{X}_1) \right\|_{q} \leq C$ and
$\left\| \nu^{Y_2}(\underline{D}_2,X_0) - \nu^{Y_2}_0(\underline{D}_2,X_0) \right\|_{q} \leq C.$
Consider
\begin{eqnarray}
E\Big[ \psi^{\underline{d}_2}(W, \eta, \Psi_{0}^{\underline{d}_2})\Big] &=& E\Bigg[ \underbrace{ \frac{ I\{D_1=d_1\} \cdot I\{D_2=d_2\}}{p^{d_1}(X_0)\cdot p^{d_2}(d_1,\underline{X}_1)} \cdot Y_2 }_{=I_1} \notag\\
& + & \underbrace{ \frac{I\{D_1=d_1\}}{p^{d_1}(X_0)} \cdot \bigg(1- \frac{I\{D_2=d_2\}}{p^{d_2}(d_1,\underline{X}_1) } \bigg) \cdot \mu^{Y_2}(\underline{d}_2,\underline{X}_1) }_{=I_2} \notag\\
& + & \underbrace{ \bigg(1- \frac{I\{D_1=d_1\}}{p^{d_1}(X_0)}\bigg) \nu^{Y_2}(\underline{d}_2,X_0)}_{=I_3} - \Psi^{\underline{d}_2}_{0} \Bigg] \notag
\end{eqnarray}
and thus
\begin{eqnarray}
\left\| \psi^{\underline{d}_2}(W, \eta, \Psi_{0}^{\underline{d}_2}) \right\|_{q} &\leq& \left\| I_1 \right\|_{q} + \left\| I_2 \right\|_{q} + \left\| I_3 \right\|_{q} + \left\| \Psi^{\underline{d}_2}_{0} \right\|_{q} \notag \\
&\leq& \frac{1}{\epsilon^2} \left\| Y_2 \right\|_{q} \notag + \frac{1- \epsilon}{\epsilon^2} \left\| \mu^{Y_2}(\underline{d}_2,\underline{X}_1) \right\|_{q} + \\
&+& \frac{1-\epsilon}{\epsilon} \left\| \nu^{Y_2}(\underline{d}_2,X_0) \right\|_{q} + | \Psi^{\underline{d}_2}_{0} | \notag \\
&\leq& C \left( \frac{1}{\epsilon^2} + \frac{2(1-\epsilon)}{\epsilon^{2/q}} \left(\frac{1}{\epsilon^2} + \frac{1}{\epsilon} \right) + \frac{1}{\epsilon} \right), \notag
\end{eqnarray}
because of triangular inequality and because the following set of inequalities hold:
\begin{eqnarray}
\left\| \mu^{Y_2}(\underline{d}_2,\underline{X}_1) \right\|_{q} &\leq& \left\| \mu^{Y_2}(\underline{d}_2,\underline{X}_1) - \mu^{Y_2}_0(\underline{d}_2,\underline{X}_1) \right\|_{q} + \left\| \mu^{Y_2}_0(\underline{d}_2,\underline{X}_1) \right\|_{q} \leq 2C/\epsilon^{2/q}, \\
\left\| \nu^{Y_2}(\underline{d}_2,X_0) \right\|_{q} &\leq& \left\| \nu^{Y_2}(\underline{d}_2,X_0) - \nu^{Y_2}_0(\underline{d}_2,X_0) \right\|_{q} + \left\| \nu^{Y_2}_0(\underline{d}_2,X_0) \right\|_{q} \leq 2C/\epsilon^{2/q}, \notag \\
|\Psi^{\underline{d}_2}_{0} | &=& |E[ \nu^{Y_2}_0(\underline{d}_2,X_0)] | \leq E_ \Big[\left| \nu^{Y_2}_0(\underline{d}_2,X_0) \right|^1 \Big]^{\frac{1}{1}} = \left\| \nu^{Y_2}_0(\underline{d}_2,X_0) \right\|_{1} \notag \\
&\leq& \left\| \nu^{Y_2}_0(\underline{d}_2,X_0) \right\|_{2} \leq \left\| Y_2 \right\|_{2}/\epsilon^{2/2} \overbrace{ \leq}^{q > 2} \left\| Y_2 \right\|_{q}/\epsilon \leq C /\epsilon. \notag
\end{eqnarray}
which gives the upper bound on $m_n$ in Assumption 3.2(b) of Chetal2018.
\textbf{Bound for $m'_n$:}
Notice that
$$\Big(E[ |\psi_a^{\underline{d}_2}(W, \eta) |^q] \Big)^{1/q}=1$$
and this gives the upper bound on $m'_n$ in Assumption 3.2(b).
\textbf{Assumption 3.2(c)}
In the following, we omit arguments for the sake of brevity and use $p^{d_1}= p^{d_1}(X_0),p^{d_2}= p^{d_2}(d_1,\underline{X}_1),\nu^{Y_2} = \nu^{Y_2}(\underline{d}_2,X_0), \mu^{Y_2} = \mu^{Y_2}(\underline{d}_2,\underline{X}_1)$ and similarly for $p^{d_1}_0,p^{d_2}_0,\nu^{Y_2}_0,\mu^{Y_2}_0.$
\textbf{Bound for $r_n$:}
For any $\eta = (p^{d_1}, p^{d_2},\mu^{Y_2}, \nu^{Y_2})$ we have
$$ \Big| E\Big( \psi_a^{\underline{d}_2}(W, \eta) - \psi_a^{\underline{d}_2}(W, \eta_0) \Big) \Big| = |1-1| = 0 \leq \delta'_N,$$
and thus we have the bound on $r_n$ from Assumption 3.2(c).
\textbf{Bound for $r'_n$:}
\begin{eqnarray}
&& \left\| \psi^{\underline{d}_2}(W, \eta, \Psi_{0}^{\underline{d}_2}) - \psi^{\underline{d}_2}(W, \eta_0, \Psi_{0}^{\underline{d}_2}) \right\|_{2} \leq \left\| I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot Y \cdot \left( \frac{1}{p^{d_1} p^{d_2}} - \frac{1}{p_0^{d_1} p_0^{d_2}} \right) \right\|_{2} \\
&+& \left\| I\{D_1=d_1\} \cdot I\{D_2=d_2\} \left( \frac{\mu^{Y_2}}{p^{d_1} p^{d_2}} - \frac{\mu^{Y_2}_0}{p_0^{d_1} p_0^{d_2}} \right) \right\|_{2} + \left\| I\{D_1=d_1\} \left( \frac{\mu^{Y_2}}{p^{d_1}} - \frac{\mu^{Y_2}_0}{p_0^{d_1}} \right) \right\|_{2} \notag \\
&+& \left\| I\{D_1=d_1\} \left( \frac{\nu^{Y_2}}{p^{d_1}} - \frac{\nu^{Y_2}_0}{p_0^{d_1}} \right) \right\|_{2} + \left\| \nu^{Y_2} - \nu^{Y_2}_0 \right\|_{2} \notag \\
&\leq& \left\| Y \cdot \left( \frac{1}{p^{d_1} p^{d_2}} - \frac{1}{p_0^{d_1} p_0^{d_2}} \right) \right\|_{2} + \left\| \frac{\mu^{Y_2}}{p^{d_1} p^{d_2}} - \frac{\mu^{Y_2}_0}{p_0^{d_1} p_0^{d_2}} \right\|_{2} + \left\| \frac{\mu^{Y_2}}{p^{d_1}} - \frac{\mu^{Y_2}_0}{p_0^{d_1}} \right\|_{2} + \left\| \frac{\nu^{Y_2}}{p^{d_1}} - \frac{\nu^{Y_2}_0}{p_0^{d_1}} \right\|_{2} + \left\| \nu^{Y_2} - \nu^{Y_2}_0 \right\|_{2} \notag \\
&\leq&
\frac{C}{\epsilon^4} \delta_n \left(1 + \frac{1}{\epsilon} \right) + \delta_n \left( \frac{1}{\epsilon^5} + C + \frac{C}{\epsilon} \right) +\delta_n \left( \frac{1}{\epsilon^3} + \frac{C}{\epsilon^2} \right) + \delta_n \left( \frac{1}{\epsilon^3} + \frac{C}{\epsilon^2} \right)+ \frac{\delta_n}{\epsilon}
\leq \delta_n' \notag
\end{eqnarray}
as long as $C_\epsilon$ in the definition of $\delta_n'$ is sufficiently large. This gives the bound on $r'_n$ from Assumption 3.2(c).
Here we made use of the fact that $\left\| \mu^{Y_2} - \mu^{Y_2}_0 \right\|_{2} = \left\| \mu^{Y_2}(\underline{d}_2,\underline{X}_1) - \mu^{Y_2}_0(\underline{d}_2,\underline{X}_1) \right\|_{2} \leq \delta_n/\epsilon,$ $\left\| \nu^{Y_2} - \nu^{Y_2}_0 \right\|_{2} = \left\| \nu^{Y_2}(\underline{d}_2,X_0) - \nu^{Y_2}_0(\underline{d}_2,X_0) \right\|_{2} \leq \delta_n/\epsilon$ and $\left\| p^{d_2} - p^{d_2}_0 \right\|_{2} = \left\|p^{d_2} (d_1,X_0) - p^{d_2} _0(d_1,X_0) \right\|_{2} \leq \delta_n/\epsilon$ using similar steps as in Assumption 3.1(b).
The last inequality in ((ref)) is satisfied because we can bound the first term by
\begin{eqnarray*}
&& \left\| Y \cdot \left( \frac{1}{p^{d_1} p^{d_2}} - \frac{1}{p_0^{d_1} p_0^{d_2}} \right) \right\|_{2} \leq C \left\| \frac{1}{p^{d_1} p^{d_2}} - \frac{1}{p_0^{d_1} p_0^{d_2}} \right\|_{2} \leq \frac{C}{\epsilon^4} \left\| p_0^{d_1} p_0^{d_2} - p^{d_1} p^{d_2} \right\|_{2} \\
&=& \frac{C}{\epsilon^4} \left\| p_0^{d_1} p_0^{d_2} - p^{d_1} p^{d_2} + p_0^{d_1} p^{d_2} - p_0^{d_1} p^{d_2} \right\|_{2} \leq \frac{C}{\epsilon^4}\left( \left\| p_0^{d_1} (p_0^{d_2} - p^{d_2} ) \right\|_{2} + \left\| p_0^{d_2} (p_0^{d_1} - p^{d_1}) \right\|_{2} \right) \\
&\leq& \frac{C}{\epsilon^4}\left( \left\| p_0^{d_2} - p^{d_2} \right\|_{2} + \left\| p_0^{d_1} - p^{d_1} \right\|_{2} \right) \leq \frac{C}{\epsilon^4} \delta_n \left(1 + \frac{1}{\epsilon} \right),
\end{eqnarray*}
where the first inequality follows from the second inequality in Assumption 4(a). The second term in ((ref)) is bounded by
\begin{eqnarray*}
&& \left\| \frac{\mu^{Y_2}}{p^{d_1} p^{d_2}} - \frac{\mu^{Y_2}_0}{p_0^{d_1} p_0^{d_2}} \right\|_{2} \leq \frac{1}{\epsilon^4} \left\| p_0^{d_1} p_0^{d_2} \mu^{Y_2} - p^{d_1} p^{d_2} \mu^{Y_2}_0 \right\|_{2} = \frac{1}{\epsilon^4}\left\| p_0^{d_1} p_0^{d_2} \mu^{Y_2} - p^{d_1} p^{d_2} \mu^{Y_2}_0 + p_0^{d_1} p_0^{d_2} \mu^{Y_2}_0 - p_0^{d_1} p_0^{d_2} \mu^{Y_2}_0 \right\|_{2} \\
&\leq& \frac{1}{\epsilon^4} \left( \left\| p_0^{d_1} p_0^{d_2} (\mu^{Y_2} - \mu^{Y_2}_0) \right\|_{2} + \left\| \mu^{Y_2}_0 ( p_0^{d_1} p_0^{d_2} - p^{d_1} p^{d_2} ) \right\|_{2} \right) \leq \frac{1}{\epsilon^4} \left( \left\| \mu^{Y_2} - \mu^{Y_2}_0 \right\|_{2} + C \left\| p_0^{d_1} p_0^{d_2} - p^{d_1} p^{d_2} \right\|_{2} \right) \\
&\leq& \frac{1}{\epsilon^4} \left( \frac{\delta_n}{\epsilon} + C \left\| p_0^{d_1} p_0^{d_2} - p^{d_1} p^{d_2} \right\|_{2} \right) \leq \delta_n \left( \frac{1}{\epsilon^5} + C + \frac{C}{\epsilon} \right) ,
\end{eqnarray*}
where the third inequality follows from $E[Y^2_2| D_1 =d_1, D_2=d_2, \underline{X_1}] \geq (E[Y_2| D_1 =d_1, D_2=d_2, \underline{X_1}])^2= \mu^2_0(\underline{d}_2, \underline{X_1}) $ by the conditional Jensen's inequality and therefore $\left\| \mu^{Y_2}_0 (\underline{d}_2,\underline{X}_1) \right\|_\infty \leq C^2.$
For the third term we get
\begin{eqnarray*}
&& \left\| \frac{\mu^{Y_2}}{p^{d_1}} - \frac{\mu^{Y_2}_0}{p_0^{d_1}} \right\|_{2} = \frac{1}{\epsilon^2} \left\| p_0^{d_1} \mu^{Y_2}- p^{d_1} \mu^{Y_2}_0 \right\|_{2} = \frac{1}{\epsilon^2} \left\| p_0^{d_1} \mu^{Y_2}- p^{d_1} \mu^{Y_2}_0 + p_0^{d_1} \mu^{Y_2}_0 - p_0^{d_1} \mu^{Y_2}_0 \right\|_{2} \\
&\leq&\frac{1}{\epsilon^2} \left( \left\| p_0^{d_1}(\mu^{Y_2} - \mu^{Y_2}_0) \right\|_{2} + \left\| \mu^{Y_2}_0 (p_0^{d_1} - p^{d_1}) \right\|_{2} \right) \leq \frac{1}{\epsilon^2} \left( \left\| \mu^{Y_2} - \mu^{Y_2}_0 \right\|_{2} + C \left\| p_0^{d_1} - p^{d_1} \right\|_{2} \right) \leq \delta_n \left( \frac{1}{\epsilon^3} + \frac{C}{\epsilon^2} \right),
\end{eqnarray*}
and similarly, for the fourth term we obtain
\begin{eqnarray*}
&& \left\| \frac{\nu^{Y_2}}{p^{d_1}} - \frac{\nu^{Y_2}_0}{p_0^{d_1}} \right\|_{2} \leq \delta_n \left( \frac{1}{\epsilon^3} + \frac{C}{\epsilon^2} \right),
\end{eqnarray*}
where we used Jensen's inequality twice to get $\left\| \nu^{Y_2}_0 (\underline{d}_2,X_0) \right\|_\infty \leq C^2$.
\textbf{Bound for $\lambda'_n$:}
Now consider
\begin{equation}
f(r) := E[\psi(W;\Psi_0^{\underline{d}_2},\eta + r(\eta-\eta_0)]. \notag
\end{equation}
For any $r \in (0,1):$
\begin{eqnarray}
\frac{\partial^2 f(r)}{\partial r^2}&=& E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\} (-2) \frac{(\mu^{Y_2}-\mu^{Y_2}_0)(p^{d_1} - p^{d_1}_0)}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2\left(p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)} \Bigg] \\
&+& E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\} (-2) \frac{(\mu^{Y_2}-\mu^{Y_2}_0)(p^{d_2} - p^{d_2}_0)}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)\left(p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)^2} \Bigg] \notag \\
&+& E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\} 2 \frac{(Y_2 - \mu^{Y_2}_0 - r(\mu^{Y_2}-\mu^{Y_2}_0) )(p^{d_1} - p^{d_1}_0)^2}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^3\left(p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)} \Bigg] \notag \\
&+& E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\} 2 \frac{(Y_2 - \mu^{Y_2}_0 - r(\mu^{Y_2}-\mu^{Y_2}_0) )(p^{d_2} - p^{d_2}_0)^2}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)\left(p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)^3} \Bigg] \notag \\
&+& E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\} 2 \frac{(Y_2 - \mu^{Y_2}_0 - r(\mu^{Y_2}-\mu^{Y_2}_0) )(p^{d_1} - p^{d_1}_0)(p^{d_2} - p^{d_2}_0)}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2\left(p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)^2} \Bigg] \notag \\
&+& E\Bigg[ I\{D_1=d_1\} (-2) \frac{(\mu^{Y_2}-\mu^{Y_2}_0)(p^{d_1} - p^{d_1}_0)}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2} \Bigg] + E\Bigg[ I\{D_1=d_1\} 2 \frac{(\nu^{Y_2}-\nu^{Y_2}_0)(p^{d_1} - p^{d_1}_0)}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2} \Bigg] \notag \\
&+& E\Bigg[ I\{D_1=d_1\} 2 \frac{r(\mu^{Y_2}-\mu^{Y_2}_0)(p^{d_1} - p^{d_1}_0)^2}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^3} \Bigg] + E\Bigg[ I\{D_1=d_1\} 2 \frac{(r(\nu^{Y_2}-\nu^{Y_2}_0)(p^{d_1} - p^{d_1}_0)^2}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^3} \Bigg] \notag \\
&+& E\Bigg[ I\{D_1=d_1\} 2 \frac{(\mu^{Y_2}_0 - \nu^{Y_2}_0 )(p^{d_1} - p^{d_1}_0)^2}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^3} \Bigg] \notag
\end{eqnarray}
Note that because
\begin{eqnarray}
E[Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)|D_1=d_1,D_2=d_2,\underline{X}_1] &= & 0, \notag \\
|p^{d_1} - p^{d_1}_0| \leq 2, \ \ \ \ \ \ |p^{d_2} - p^{d_2}_0| &\leq & 2 \notag \\
\left\| \mu^{Y_2}_0 \right\|_{q} \leq \left\| Y_2 \right\|_{q}/\epsilon^{1/q} &\leq & C/\epsilon^{2/q} \notag \\
\left\| \nu^{Y_2}_0 \right\|_{q} \leq \left\| Y_2 \right\|_{q}/\epsilon^{1/q} &\leq & C/\epsilon^{2/q} \notag \\
\left\| \mu^{Y_2}-\mu^{Y_2}_0\right\|_{2} \times \left\| p^{d_1}-p^{d_1}_0\right\|_{2} &\leq & \delta^_n n^{-1/2}/\epsilon, \notag \\
\left\| \mu^{Y_2}-\mu^{Y_2}_0\right\|_{2} \times \left\| p^{d_2}-p^{d_2}_0\right\|_{2} &\leq & \delta^_n n^{-1/2}/\epsilon^2,\notag \\
\left\| \nu^{Y_2}-\nu^{Y_2}_0\right\|_{2} \times \left\| p^{d_1}-p^{d_1}_0\right\|_{2} &\leq & \delta^_n n^{-1/2}/\epsilon.\notag
\end{eqnarray}
we get that for some constant $C_{\epsilon}''$ that only depends on $C$ and $\epsilon$
\begin{equation}
\left|\frac{\partial^2 f(r)}{\partial r^2} \right| \leq C_{\epsilon}” \delta_n n^{-1/2} \leq \delta_n' n^{-1/2} \notag
\end{equation}
and this gives the upper bound on $\lambda'_n$ in Assumption 3.2(c) of Chetal2018 as long as $C_{\epsilon} \geq C_{\epsilon}''$. We used the following inequalities
\begin{eqnarray}
\left\| \mu^{Y_2}-\mu^{Y_2}_0\right\|_{2} &=& \left\|\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{d}_2,\underline{X}_1)\right\|_{2} \leq \left\|\mu^{Y_2}(\underline{D}_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{D}_2,\underline{X}_1)\right\|_{2}/\epsilon \notag \\
\left\| \nu^{Y_2}-\nu^{Y_2}_0\right\|_{2} &=& \left\|\nu^{Y_2}(\underline{d}_2,X_0)-\nu^{Y_2}_0(\underline{d}_2,X_0)\right\|_{2} \leq \left\|\nu^{Y_2}(\underline{D}_2,X_0)-\nu^{Y_2}_0(\underline{D}_2,X_0)\right\|_{2}/\epsilon^2 \notag \\
\left\| p^{d_2}-p^{d_2}_0\right\|_{2} &=& \left\|p^{d_2}(d_1,X_0)-p^{d_2}_0(d_1,X_0)\right\|_{2} \leq \left\|p^{d_2}(D_1,X_0)-p^{d_2}_0(D_1,X_0)\right\|_{2}/\epsilon, \notag
\end{eqnarray}
and these can be shown using similar steps as in Assumption 3.1(b).
To verify that $\left|\frac{\partial^2 f(r)}{\partial r^2} \right| \leq C_{\epsilon}'' \delta_n n^{-1/2}$ holds, note that by the triangular inequality it is sufficient to bound the absolute value of each of the ten terms in ((ref)) separately. We illustrate it for the first, third, and last terms. For the first term:
\begin{eqnarray}
&& \left| E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\} (-2) \frac{(\mu^{Y_2}-\mu^{Y_2}_0)(p^{d_1} - p^{d_1}_0)}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2\left(p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)} \Bigg] \right| \notag \\
&\leq& 2 \left| E\Bigg[ \frac{(\mu^{Y_2}-\mu^{Y_2}_0)(p^{d_1} - p^{d_1}_0)}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2(p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)} \Bigg] \right| \notag \\
&\leq& \frac{2}{ \epsilon^3} \left| E\Bigg[ (\mu^{Y_2}-\mu^{Y_2}_0)(p^{d_1} - p^{d_1}_0) \Bigg] \right| \leq \frac{2}{\epsilon^3} \frac{\delta^_N}{\epsilon} n^{-1/2}. \notag
\end{eqnarray}
For the second inequality we used the fact that for $i \in \{1,2\}: 1 \geq p^{d_i}_0 + r(p^{d_i} -p^{d_i}_0) = (1-r)p^{d_i}_0 + r p^{d_i} \geq (1-r)\epsilon + r \epsilon = \epsilon$ and in the third Holder's inequality. For the third term, we get
\begin{eqnarray}
&& \left| E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\} 2 \frac{(Y_2 - \mu^{Y_2}_0 - r(\mu^{Y_2}-\mu^{Y_2}_0) )(p^{d_1} - p^{d_1}_0)^2}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^3\left(p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)} \Bigg] \right| \notag \\
&\leq& \frac{2}{\epsilon^4} \left| E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\}(Y_2 - \mu^{Y_2}_0 - r(\mu^{Y_2}-\mu^{Y_2}_0) )(p^{d_1} - p^{d_1}_0)^2 \Bigg] \right| \notag \\
&\leq& \frac{8}{\epsilon^4} \left| E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\}(Y_2 - \mu^{Y_2}_0) \Bigg] \right| + \frac{2}{\epsilon^4} \left| E\Bigg[r(\mu^{Y_2}-\mu^{Y_2}_0) (p^{d_1} - p^{d_1}_0)^2 \Bigg] \right| \notag \\
&\leq& \frac{2 \cdot 2}{\epsilon^4} \left| E\Bigg[1\cdot(\mu^{Y_2}-\mu^{Y_2}_0) )(p^{d_1} - p^{d_1}_0) \Bigg] \right| \leq \frac{4}{\epsilon^4} \frac{\delta^_N}{\epsilon} n^{-1/2}, \notag
\end{eqnarray}
where in addition we made use of conditions ((ref)).
For the last term, we have
\begin{eqnarray}
&& E\Bigg[ I\{D_1=d_1\} 2 \frac{(\mu^{Y_2}_0 - \nu^{Y_2}_0 )(p^{d_1} - p^{d_1}_0)^2}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^3} \Bigg] \notag \\
&=& E\Bigg[ \overbrace{ I\{D_1=d_1\} \frac{(\mu^{Y_2}_0 - \nu^{Y_2}_0 )}{p^{d_1}_0} }^{\int E\big[ \mu_0^{Y_2}(\underline{d}_2,\underline{x}_1)-\nu_0^{Y_2}(\underline{d}_2,x_0) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0=x_0}=0} \cdot \frac{2p^{d_1}_0(p^{d_1} - p^{d_1}_0)^2}{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^3} \Bigg] = 0. \notag
\end{eqnarray}
The remaining terms in ((ref)) are bounded similarly.
\textbf{Assumption 3.2(d)}
\begin{eqnarray}
E\Big[ (\psi^{\underline{d}_2}(W, \eta_0, \Psi_{0}^{\underline{d}_2}) )^2\Big] &=& E\Bigg[ \Bigg( \underbrace{ \frac{ I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} }_{=I_1} \notag\\
& + & \underbrace{ \frac{I\{D_1=d_1\}\cdot [\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}{p_0^{d_1}(X_0)} }_{=I_2} \notag\\
& + & \underbrace{ \nu_0^{Y_2}(\underline{d}_2,X_0) - \Psi^{\underline{d}_2}_{0}}_{=I_3} \Bigg)^2 \Bigg] \notag\\
& = & E[I_1^2 + I_2^2 + I_3^2] \geq E[I^2_1]\notag\\
& = & E\Bigg[ I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot \Bigg( \frac{ [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \Bigg)^2 \Bigg] \notag\\
& \geq & \epsilon^2 E\Bigg[ \Bigg( \frac{ [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \Bigg)^2 \Bigg] \notag\\
&\geq& \frac{\epsilon^2 c^2}{(1-\epsilon)^4} > 0. \notag
\end{eqnarray}
because $\Pr(\underline{D}_2 = \underline{d}_2|\underline{X}_1)= p_0^{d_1} (X_0) \cdot p_0^{d_2} (d_1,\underline{X}_1) \geq \epsilon^2, \ p_0^{d_1}(X_0) \leq 1-\epsilon$ and $p_0^{d_2}(d_1,\underline{X}_1) \leq 1-\epsilon.$
where the second equality follows from
\begin{eqnarray}
E\Big[ I_1 \cdot I_2\Big] &=& E\Bigg[ \overbrace{\frac{ I\{D_1=d_1\} \cdot I\{D_2=d_2\}}{ (p_0^{d_1}(X_0))^2\cdot p_0^{d_2}(d_1,\underline{X}_1)} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}^{E[\cdot|X_0]=E[E[Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)|\underline{D}_2=\underline{d}_2,\underline{X}_1]|D_1=d_1,X_0]=0} \cdot [\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)] \Bigg], \notag\\
E\Big[ I_2 \cdot I_3\Big] &=& E\Bigg[ \overbrace{ \frac{ I\{D_1=d_1\}}{p_0^{d_1}(X_0)} \cdot [\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}^{E[\cdot|\underline{X}_0]=\int E\big[ \mu_0^{Y_2}(\underline{d}_2,\underline{x}_1)-\nu_0^{Y_2}(\underline{d}_2,x_0) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0=x_0}=0} \cdot [ \nu_0^{Y_2}(\underline{d}_2,X_0) - \Psi^{\underline{d}_2}_{0}] \Bigg],\notag\\
E\Big[ I_1 \cdot I_3\Big] &=& E\Bigg[ \overbrace{\frac{ I\{D_1=d_1\} \cdot I\{D_2=d_2\}}{ p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}^{E[\cdot|X_0]=E[E[Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)|\underline{D}_2=\underline{d}_2,\underline{X}_1]|D_1=d_1,X_0]=0} \cdot [\nu_0^{Y_2}(\underline{d}_2,X_0) - \Psi^{\underline{d}_2}_{0}] \Bigg]. \notag
\end{eqnarray}
\subsection{Proof of Theorem 2}
The proof follows in a similar manner than the one of Theorem 1 (Section (ref)). All bounds hold uniformly over all probability laws $P \in \mathcal{P}$ where $\mathcal{P}$ is the set of all possible probability laws, and we omit $P$ for brevity.
Denote by $S$ a binary indicator for being selected into the target population and by $g(X_0)=\Pr(S=1|X_0)$ the selection probability as a function of $X_0$.
Define the nuisance parameter to be $\chi=(g,\eta)=(g(X_0),p^{d_1}(X_0), p^{d_2}(D_1,\underline{X}_1), \mu^{Y_2}(\underline{D}_2,\underline{X}_1),\nu^{Y_2}(\underline{D}_2,X_0))$. The score function for the weighted counterfactual $\Psi^{\underline{d}_2, S=1}_{0}=E[Y_2(\underline{d}_2)|S=1]=E[g(X_0)\cdot Y_2(\underline{d}_2)/\Pr(S=1)]$ is given by:
\begin{eqnarray}
\psi^{\underline{d}_2, S=1}(W, \chi, \Psi^{\underline{d}_2,S=1}_{0}) &=& \frac{g(X_0)}{\Pr(S=1)}\cdot\frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p^{d_1}(X_0)\cdot p^{d_2}(d_1,\underline{X}_1)} \notag\\
& + & \frac{g(X_0)}{\Pr(S=1)}\cdot\frac{I\{D_1=d_1\}\cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu^{Y_2}(\underline{d}_2,X_0)]}{p^{d_1}(X_0)} \notag\\
& + &\frac{S}{\Pr(S=1)}\cdot\nu^{Y_2}(\underline{d}_2,X_0) - \Psi^{\underline{d}_2, S=1}_{0}. \notag
\end{eqnarray}
Let $\mathcal{T}^*_n$ be the set fo all $\chi= (g,\eta)=(g, p^{d_1}, p^{d_2},\mu^{Y_2}, \nu^{Y_2})$ consisting of $P$-square integrable functions $g, p^{d_1}, p^{d_2},\mu^{Y_2}$ and $\nu^{Y_2}$ such that
\begin{eqnarray}
\left\| \chi - \chi_0 \right\|_{q} &\leq& C, \\
\left\| \chi - \chi_0 \right\|_{2} &\leq& \delta_n, \notag \\
\left\| g(X_0)-1/2\right\|_{\infty} &\leq& 1/2-\epsilon, \notag\\
\left\| p^{d_1}(X_0)-1/2\right\|_{\infty} &\leq& 1/2-\epsilon, \notag\\
\left\| p^{d_2}(D_1,\underline{X}_1)-1/2)\right\|_{\infty} &\leq & 1/2-\epsilon, \notag \\
\left\| \mu^{Y_2}(\underline{D}_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{D}_2,\underline{X}_1)\right\|_{2} \times \left\| p^{d_1}(X_0)-p^{d_1}_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}, \notag \\
\left\| \mu^{Y_2}(\underline{D}_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{D}_2,\underline{X}_1)\right\|_{2} \times \left\| p^{d_2}(D_1,\underline{X}_1)-p^{d_2}_0(D_1,\underline{X}_1)\right\|_{2} &\leq & \delta^_n n^{-1/2},\notag \\
\left\| \nu^{Y_2}(\underline{D}_2,X_0)-\nu^{Y_2}_0(\underline{D}_2,X_0)\right\|_{2} \times \left\| p^{d_1}(X_0)-p^{d_1}_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}.\notag \\
\left\| \mu^{Y_2}(\underline{D}_2,\underline{X}_1)-\mu^{Y_2}_0(\underline{D}_2,\underline{X}_1)\right\|_{2} \times \left\| g(X_0)-g_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}, \notag \\
\left\| \nu^{Y_2}(\underline{D}_2,X_0)-\nu^{Y_2}_0(\underline{D}_2,X_0)\right\|_{2} \times \left\| g(X_0)-g_0(X_0)\right\|_{2} &\leq & \delta^_n n^{-1/2}.\notag
\end{eqnarray}
We furthermore replace the sequence $(\delta_n)_{n \geq 1}$ by $(\delta_n')_{n \geq 1},$ where $\delta_n' = C_{\epsilon} \max(\delta_n,n^{-1/2}),$ where $C_{\epsilon}$ is sufficiently large constant that only depends on $C$ and $\epsilon.$
\textbf{Assumption 3.1: Linear scores and Neyman orthogonality}
\textbf{Assumption 3.1(a)}
\textbf{Moment Condition:}
The moment condition $E\Big[\psi^{\underline{d}_2,S=1}(W, \chi_0, \Psi^{\underline{d}_2,S=1}_{0})\Big] =0$ holds by the law of iterated expectations:
\begin{eqnarray}
&&E\Big[\psi^{\underline{d}_2,S=1}(W, \chi_0, \Psi^{\underline{d}_2,S=1}_{0})\Big]\notag\\
&=& E\Bigg[ \frac{g(X_0)}{\Pr(S=1)}\cdot \overbrace{ E\Bigg[\frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} }{ p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \cdot [Y_2- \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]\Bigg|\underline{X}_1\Bigg]}^{=E[E[Y_2- \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)|\underline{D}_2=\underline{d}_2,\underline{X}_1]|D_1=d_1,X_0]=0} \Bigg]\notag\\
&+& \ E\Bigg[\frac{g(X_0)}{\Pr(S=1)}\cdot \overbrace{ E\Bigg[ \frac{I\{D_1=d_1\}\cdot [ \mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)- \nu_0^{Y_2}(\underline{d}_2,X_0)]}{ p_0^{d_1}(X_0)} \Bigg| X_0 \Bigg]}^{= \int E\Big[ \mu_0^{Y_2}(\underline{d}_2,\underline{x}_1)- \nu_0^{Y_2}(\underline{d}_2,x_0) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0=x_0}=0} \Bigg] \notag\\
&+& \ E\Bigg[ \frac{S}{\Pr(S=1)}\cdot \nu_0^{Y_2}(\underline{d}_2,X_0) \Bigg] - \Psi^{\underline{d}_2,S=1}_{0} \ \ = \ \ \Psi^{\underline{d}_2,S=1}_{0}\ \ - \ \ \Psi^{\underline{d}_2,S=1}_{0} \ \
= 0. \notag
\end{eqnarray}
\textbf{Assumption 3.1(b)}
\textbf{Linearity:} The score $ \psi^{\underline{d}_2, S=1}(W, \chi_0, \Psi^{\underline{d}_2, S=1}_{0}) $ is linear in $\Psi^{\underline{d}_2, S=1}_{0}$:
$\psi^{\underline{d}_2,S=1}(W, \chi_0, \Psi^{\underline{d}_2,S=1}_{0}) = \psi^{\underline{d}_2,S=1}_a(W, \chi_0) \cdot\Psi^{\underline{d}_2,S=1}_0 + \psi^{\underline{d}_2,S=1}_b(W, \chi_0) $
with $\psi^{\underline{d}_2,S=1}_a(W, \chi_0) = -1$ and
\begin{eqnarray}
\psi^{\underline{d}_2,S=1}_b(W, \chi_0) &=&\frac{g(X_0)}{\Pr(S=1)}\cdot\frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)}\notag\\
& + & \frac{g(X_0)}{\Pr(S=1)}\cdot\frac{I\{D_1=d_1\}\cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu^{Y_2}(\underline{d}_2,X_0)]}{p^{d_1}(X_0)} \notag\\
& + & \frac{S}{\Pr(S=1)}\cdot\nu^{Y_2}(\underline{d}_2,X_0). \notag
\end{eqnarray}
\textbf{Assumption 3.1(c)}
\textbf{Continuity:}
We may observe that the expression for the second Gateaux derivative of a map $\chi \mapsto E[\psi^{\underline{d}_2,S=1}(W, \chi, \Psi^{\underline{d}_2,S=1})]$, given in ((ref)), is continuous.
\textbf{Assumption 3.1(d)}
\textbf{Neyman Orthogonality}: For any $\eta \in \mathcal{T}^*_N,$ the Gateaux derivative in the direction $ \chi - \chi_0 = (g(X_0)-g_0(X_0),p^{d_1}(X_0)-p_0^{d_1}(X_0), p^{d_2}(D_1,\underline{X}_1)-p_0^{d_2}(D_1,\underline{X}_1),\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1), \nu^{Y_2}(\underline{d}_2,X_0)-\nu_0^{Y_2}(\underline{d}_2,X_0))$ is given by
\begin{align}
&\partial E \big[\psi^{\underline{d}_2,S=1}(W, \chi,\Psi^{\underline{d}_2,S=1}_{0})\big] \big[\chi - \chi_0 \big] = \notag\\
& - E \Bigg[\frac{g_0(X_0)}{\Pr(S=1)}\cdot \frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \Bigg] \tag{$*$}\\
& + E \Bigg[ \frac{g_0(X_0)}{\Pr(S=1)}\cdot \frac{I\{D_1=d_1\} \cdot [\mu^{Y_2}(\underline{d}_2,\underline{X}_1)-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)} \Bigg] \tag{$**$}\\
&- \ E \Bigg[ \frac{g_0(X_0)}{\Pr(S=1)}\cdot \frac{\overbrace{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}^{E[\cdot|X_0]=0}}{ p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1) }\cdot\frac{[p^{d_1}(X_0)-p_0^{d_1}(X_0)] }{p_0^{d_1}(X_0)} \Bigg] \notag\\
& - \ E \Bigg[ \frac{g_0(X_0)}{\Pr(S=1)}\cdot \overbrace{\frac{I\{D_1=d_1\}\cdot [\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}{p_0^{d_1}(X_0)}}^{E[\cdot|X_0]=0} \cdot \frac{[p^{d_1}(X_0)-p_0^{d_1}(X_0)] }{p_0^{d_1}(X_0)} \Bigg] \notag \\
&- \ E \Bigg[ \frac{g_0(X_0)}{\Pr(S=1)}\cdot \frac{\overbrace{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}^{E[\cdot|X_0]=0}}{ p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1) }\cdot\frac{[p^{d_2}(d_1,\underline{X}_1)-p_0^{d_2}(d_1,\underline{X}_1)] }{p_0^{d_2}(d_1,\underline{X}_1)} \Bigg] \notag\\
& - \ E \Bigg[ \frac{g_0(X_0)}{\Pr(S=1)}\cdot \underbrace{\frac{I\{D_1=d_1\} \cdot [\nu^{Y_2}(\underline{d}_2,X_0)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}{p_0^{d_1}(X_0)}}_{ E[\cdot|X_0]=\frac{p_0^{d_1}(X_0)}{p_0^{d_1}(X_0)}\cdot[\nu^{Y_2}(\underline{d}_2,X_0)-\nu_0^{Y_2}(\underline{d}_2,X_0)]} \Bigg] \tag{$***$}\\
& + E\Big[ \overbrace{\frac{S}{\Pr(S=1)}}^{E[\cdot|X_0]=\frac{g_0(X_0)}{\Pr(S=1)}}\cdot [\nu^{Y_2}(\underline{d}_2,X_0)-\nu_0^{Y_2}(\underline{d}_2,X_0)]\big] \tag{$****$}\\
&+E \Bigg[ \frac{\overbrace{I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}^{E[\cdot| X_0]=0}}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)}\cdot\frac{[g(X_0)-g_0(X_0)]}{\Pr(S=1)} \Bigg]\notag\\
& + E \Bigg[\underbrace{\frac{I\{D_1=d_1\}\cdot [\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}{p_0^{d_1}(X_0)}}_{E[\cdot|X_0]=0} \cdot\frac{[g(X_0)-g_0(X_0)]}{\Pr(S=1)} \Bigg] =0,\notag
\end{align}
where terms $(*)$ and $(**)$ as well as $(***)$ and $(****)$ cancel out.
\textbf{Assumption 3.1(e)}
\textbf{Singular values of $E[\psi^{\underline{d}_2,S=1}_a(W;\chi_0)]$ are bounded:}
Holds trivially, because $\psi^{\underline{d}_2,S=1}_a(W;\chi_0) = -1.$
\newline
\textbf{Assumption 3.2: Score regularity and quality of nuisance parameter estimators}
\textbf{Assumption 3.2(a)}
This assumption directly follows from the defition of $\mathcal{T}^*_n$ and the regularity conditions (Assumption 5).
\textbf{Assumption 3.2(b)}
\textbf{Bounds for $m_n$ :}
We start by rearranging the terms in the Neyman score function ((ref))
\begin{eqnarray}
E\Big[ \psi^{\underline{d}_2,S=1}(W, \chi, \Psi_{0}^{\underline{d}_2,S=1})\Big] &=& E\Bigg[ \underbrace{ \frac{g(X_0)}{\Pr(S=1)}\cdot \frac{ I\{D_1=d_1\} \cdot I\{D_2=d_2\}}{p^{d_1}(X_0)\cdot p^{d_2}(d_1,\underline{X}_1)} \cdot Y_2 }_{=I_1} \notag\\
& + & \underbrace{\frac{g(X_0)}{\Pr(S=1)}\cdot \frac{I\{D_1=d_1\}}{p^{d_1}(X_0)} \cdot \bigg(1- \frac{I\{D_2=d_2\}}{p^{d_2}(d_1,\underline{X}_1) } \bigg) \cdot \mu^{Y_2}(\underline{d}_2,\underline{X}_1) }_{=I_2} \notag\\
& + & \underbrace{ \bigg( \frac{S}{\Pr(S=1)} - \frac{g(X_0)}{\Pr(S=1)}\cdot \frac{I\{D_1=d_1\}}{p^{d_1}(X_0)}\bigg) \nu^{Y_2}(\underline{d}_2,X_0)}_{=I_3} - \Psi^{\underline{d}_2,S=1}_{0} \Bigg] \notag
\end{eqnarray}
and then, Following the same steps as in ((ref)), we get
\begin{eqnarray}
\left\| \psi^{\underline{d}_2,S=1}(W, \chi, \Psi_{0}^{\underline{d}_2,S=1}) \right\|_{q} &\leq& \left\| I_1 \right\|_{q} + \left\| I_2 \right\|_{q} + \left\| I_3 \right\|_{q} + \left\| \Psi^{\underline{d}_2,S=1}_{0} \right\|_{q} \notag \\
&\leq& \frac{1}{\epsilon^3} \left\| Y_2 \right\|_{q} \notag + \frac{1- \epsilon}{\epsilon^3} \left\| \mu^{Y_2}(\underline{d}_2,\underline{X}_1) \right\|_{q} + \\
&+& \frac{1-\epsilon}{\epsilon^2} \left\| \nu^{Y_2}(\underline{d}_2,X_0) \right\|_{q} + | \Psi^{\underline{d}_2,S=1}_{0} | \notag \\
&\leq& C \left( \frac{1}{\epsilon^3} + \frac{2(1-\epsilon)}{\epsilon^{2/q}} \left(\frac{1}{\epsilon^3} + \frac{1}{\epsilon^2} \right) + \frac{1}{\epsilon^2} \right) \notag
\end{eqnarray}
because of triangular inequality and because the following set of inequalities hold (similarly to ((ref))):
\begin{eqnarray*}
\left\| \mu^{Y_2}(\underline{d}_2,\underline{X}_1) \right\|_{q} &\leq& 2C/\epsilon^{2/q}, \ \ \left\| \nu^{Y_2}(\underline{d}_2,X_0) \right\|_{q} \leq 2C/\epsilon^{2/q}, \notag \\
|\Psi^{\underline{d}_2,S=1}_{0} | &=& \left|E\left[ \frac{S}{\Pr(S=1)} \nu^{Y_2}_0(\underline{d}_2,X_0) \right] \right| \leq E_ \Big[\left| \nu^{Y_2}_0(\underline{d}_2,X_0) \right|^1 \Big]^{\frac{1}{1}} / \epsilon= \left\| \nu^{Y_2}_0(\underline{d}_2,X_0) \right\|_{1}/ \epsilon \notag \\
&\leq& \left\| \nu^{Y_2}_0(\underline{d}_2,X_0) \right\|_{2} / \epsilon \leq \left\| Y_2 \right\|_{2}/\epsilon^{4/2} \overbrace{ \leq}^{q > 2} \left\| Y_2 \right\|_{q}/\epsilon^{2} \leq C /\epsilon^{2}. \notag
\end{eqnarray*}
which gives the upper bound on $m_n$ in Assumption 3.2(b) of Chetal2018.
\textbf{Bounds for $m'_n$:}
Notice that
$$\Big(E[ |\psi_a^{\underline{d}_2,S=1}(W, \chi) |^q] \Big)^{1/q}=1$$
and this gives the upper bound on $m'_n$ in Assumption 3.2(b) of Chetal2018.
\textbf{Assumption 3.2(c)}
\textbf{Bound for $r_n$:}
For any $\chi = (g, p^{d_1}, p^{d_2},\mu^{Y_2}, \nu^{Y_2})$ we have
$$ \Big| E\Big( \psi_a^{\underline{d}_2,S=1}(W, \chi) - \psi_a^{\underline{d}_2,S=1}(W, \chi_0) \Big) \Big| = |1-1| = 0 \leq \delta'_N,$$
and thus we have the bound on $r_n$ from Assumption 3.2(c) of Chetal2018.
\textbf{Bound for $r'_n$:}
\begin{eqnarray*}
&& \left\| \psi^{\underline{d}_2,S=1}(W, \chi, \Psi_{0}^{\underline{d}_2,S=1}) - \psi^{\underline{d}_2,S=1}(W, \chi_0, \Psi_{0}^{\underline{d}_2,S=1}) \right\|_{2} \leq
\left\| \frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\}}{\Pr(S=1)} \cdot Y \cdot \left( \frac{g}{p^{d_1} p^{d_2}} - \frac{g_0}{p_0^{d_1} p_0^{d_2}} \right) \right\|_{2} \notag \\
&+& \left\| \frac{I\{D_1=d_1\} \cdot I\{D_2=d_2\}}{\Pr(S=1)} \left( \frac{g \cdot \mu^{Y_2}}{p^{d_1} p^{d_2}} - \frac{g_0 \cdot \mu^{Y_2}_0}{p_0^{d_1} p_0^{d_2}} \right) \right\|_{2} + \left\| \frac{I\{D_1=d_1\}}{\Pr(S=1)} \left( \frac{g \cdot \mu^{Y_2}}{p^{d_1}} - \frac{g_0 \cdot \mu^{Y_2}_0}{p_0^{d_1}} \right) \right\|_{2} \\ \notag
&+& \left\| \frac{I\{D_1=d_1\}}{\Pr(S=1)} \left( \frac{g \cdot \nu^{Y_2}}{p^{d_1}} - \frac{ g_0 \cdot \nu^{Y_2}_0}{p_0^{d_1}} \right) \right\|_{2} + \left\| \frac{S}{\Pr(S=1)} (\nu^{Y_2} - \nu^{Y_2}_0) \right\|_{2} \\ \notag
&\leq& \frac{1}{\epsilon} \left\| Y \cdot \left( \frac{g}{p^{d_1} p^{d_2}} - \frac{g_0}{p_0^{d_1} p_0^{d_2}} \right) \right\|_{2} + \frac{1}{\epsilon}\left\| \frac{g \cdot \mu^{Y_2}}{p^{d_1} p^{d_2}} - \frac{g_0 \cdot \mu^{Y_2}_0}{p_0^{d_1} p_0^{d_2}} \right\|_{2} + \frac{1}{\epsilon} \left\| \frac{g \cdot \mu^{Y_2}}{p^{d_1}} - \frac{g_0 \cdot \mu^{Y_2}_0}{p_0^{d_1}} \right\|_{2} \\
&+& \frac{1}{\epsilon} \left\| \frac{g \cdot \nu^{Y_2}}{p^{d_1}} - \frac{g_0 \cdot \nu^{Y_2}_0}{p_0^{d_1}} \right\|_{2} + \frac{1}{\epsilon}\left\| \nu^{Y_2} - \nu^{Y_2}_0 \right\|_{2} \\
&\leq& \frac{C}{\epsilon^5} \delta_n \left(2 + \frac{1}{\epsilon} \right) + \frac{\delta_n}{\epsilon^5} \left( \frac{1}{\epsilon} + 2C + \frac{C}{\epsilon} \right) + \frac{\delta_n}{\epsilon^3} \left( \frac{1}{\epsilon}+2C \right)+ \frac{\delta_n}{\epsilon^3} \left( \frac{1}{\epsilon}+2C \right) + \frac{\delta_n}{\epsilon^{2}} \leq \delta_n'
\end{eqnarray*}
as long as $C_\epsilon$ in the definition of $\delta_n'$ is sufficiently large. This gives the bound on $r'_n$ from Assumption 3.2(c) of Chetal2018.
The last inequality holds because we can bound the first term by
\begin{eqnarray*}
&& \left\| Y \cdot \left( \frac{g}{p^{d_1} p^{d_2}} - \frac{g_0}{p_0^{d_1} p_0^{d_2}} \right) \right\|_{2} \leq C \left\| \frac{g}{p^{d_1} p^{d_2}} - \frac{g_0}{p_0^{d_1} p_0^{d_2}} \right\|_{2} \leq \frac{C}{\epsilon^4} \left\| p_0^{d_1} p_0^{d_2} g - p^{d_1} p^{d_2} g_0 \right\|_{2} \\
&=& \frac{C}{\epsilon^4} \left\| p_0^{d_1} p_0^{d_2} g - p^{d_1} p^{d_2} g_0 + p_0^{d_1} p_0^{d_2} g - p_0^{d_1} p_0^{d_2} g_0 \right\|_{2} \leq \frac{C}{\epsilon^4} \left( \left\| g - g_0 \right\|_{2} + 1 \cdot \left\| p_0^{d_1} p_0^{d_2} - p^{d_1} p^{d_2} \right\|_{2} \right) \\
&\leq& \frac{C}{\epsilon^4}\left( \delta_n + 1 \cdot \delta_n \left(1 + \frac{1}{\epsilon} \right) \right) \leq \frac{C}{\epsilon^4} \delta_n \left(2 + \frac{1}{\epsilon} \right),
\end{eqnarray*}
the second term is bounded by
\begin{eqnarray*}
&& \left\| \frac{g \cdot \mu^{Y_2}}{p^{d_1} p^{d_2}} - \frac{g_0 \cdot \mu^{Y_2}_0}{p_0^{d_1} p_0^{d_2}} \right\|_{2} \leq \frac{1}{\epsilon^4} \left\| p_0^{d_1} p_0^{d_2} g \cdot \mu^{Y_2} - p^{d_1} p^{d_2} g_0 \cdot \mu^{Y_2}_0 \right\|_{2} \\
&=& \frac{1}{\epsilon^4}\left\| p_0^{d_1} p_0^{d_2} g \cdot \mu^{Y_2} - p^{d_1} p^{d_2} g_0 \cdot \mu^{Y_2}_0 + p_0^{d_1} p_0^{d_2} g_0 \cdot \mu^{Y_2}_0 - p_0^{d_1} p_0^{d_2} g_0 \cdot \mu^{Y_2}_0 \right\|_{2} \\
&\leq& \frac{1}{\epsilon^4} \left( \left\| p_0^{d_1} p_0^{d_2} (g \cdot \mu^{Y_2} - g_0 \cdot \mu^{Y_2}_0) \right\|_{2} + \left\| g_0 \cdot \mu^{Y_2}_0 ( p_0^{d_1} p_0^{d_2} - p^{d_1} p^{d_2} ) \right\|_{2} \right) \\
&\leq& \frac{1}{\epsilon^4} \left( \left\| g \cdot \mu^{Y_2} - g_0 \cdot \mu^{Y_2}_0 \right\|_{2} + 1 \cdot C \left\| p_0^{d_1} p_0^{d_2} - p^{d_1} p^{d_2} \right\|_{2} \right) \\
&\leq&\frac{1}{\epsilon^4} \left( \delta_n \left( C + \frac{1}{\epsilon}\right) + C \delta_n \left(1 + \frac{1}{\epsilon} \right) \right) = \frac{\delta_n}{\epsilon^4} \left( \frac{1}{\epsilon} + 2C + \frac{C}{\epsilon} \right)
\end{eqnarray*}
where $ \left\| g \cdot \mu^{Y_2} - g_0 \cdot \mu^{Y_2}_0 \right\|_{2} $ is bounded similarly as $\left\| p_0^{d_1} \mu^{Y_2}- p^{d_1} \mu^{Y_2}_0 \right\|_{2}$ and we also used bounds for $ \left\| p_0^{d_1} p_0^{d_2} - p^{d_1} p^{d_2} \right\|_{2}$ derived in section ((ref)).
while for the third term we get
\begin{eqnarray*}
&& \left\| \frac{g \cdot \mu^{Y_2}}{p^{d_1}} - \frac{g_0 \cdot \mu^{Y_2}_0}{p_0^{d_1}} \right\|_{2} = \frac{1}{\epsilon^2} \left\| p_0^{d_1}g \cdot \mu^{Y_2}- p^{d_1}g_0 \cdot \mu^{Y_2}_0 \right\|_{2} \\
&=& \frac{1}{\epsilon^2} \left\| p_0^{d_1}g \cdot \mu^{Y_2}- p^{d_1}g_0 \cdot \mu^{Y_2}_0 + p_0^{d_1}g_0 \cdot \mu^{Y_2}_0 - p_0^{d_1}g_0 \cdot \mu^{Y_2}_0 \right\|_{2} \\
&\leq&\frac{1}{\epsilon^2} \left( \left\| p_0^{d_1}(g \cdot \mu^{Y_2} - g_0 \cdot \mu^{Y_2}_0) \right\|_{2} + \left\| g_0 \cdot \mu^{Y_2}_0 (p_0^{d_1} - p^{d_1}) \right\|_{2} \right) \\
&\leq& \frac{1}{\epsilon^2} \left( \delta_n \left(C+\frac{1}{\epsilon} \right) + C \left\| p_0^{d_1} - p^{d_1} \right\|_{2} \right) \leq \frac{1}{\epsilon^2} \left(\delta_n \left(C+\frac{1}{\epsilon} \right) + C \delta_n \right) = \frac{\delta_n}{\epsilon^2} \left( \frac{1}{\epsilon}+2C \right).
\end{eqnarray*}
and similarly, for the fourth term we obtain
\begin{eqnarray*}
&& \left\| \frac{\nu^{Y_2}}{p^{d_1}} - \frac{\nu^{Y_2}_0}{p_0^{d_1}} \right\|_{2} \leq \frac{\delta_n}{\epsilon^2} \left( \frac{1}{\epsilon}+2C \right).
\end{eqnarray*}
\textbf{Bound for $\lambda'_n$:}
Now consider
\begin{equation}
f(r) := E[\psi^{\underline{d}_2,S=1}(W;\Psi_0^{\underline{d}_2,S=1},\chi_0 + r(\chi-\chi_0)] \notag
\end{equation}
For any $r \in (0,1):$
\begin{eqnarray}
\frac{\partial^2 f(r)}{\partial r^2} &=& E\Bigg[ \frac{I \{D_1 = d_1 \} }{\Pr(S=1)} \cdot \frac{ 2 (g-g_0) \Big( (\mu^{Y_2} - \mu^{Y_2}_0) - (\nu^{Y_2} - \nu^{Y_2}_0) \Big) }{p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)} \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} }{\Pr(S=1)} \cdot \frac{ (-2) \Big(g_0 + r(g-g_0) \Big) \Big( (\mu^{Y_2} - \mu^{Y_2}_0) - (\nu^{Y_2} - \nu^{Y_2}_0)\Big) (p^{d_1} -p^{d_1}_0) }{\left(p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0) \right)^2} \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} }{\Pr(S=1)} \cdot \frac{ 2 (g-g_0) \Big( (\mu^{Y_2}_0 + r(\mu^{Y_2} - \mu^{Y_2}_0)) - (\nu^{Y_2}_0 + r(\nu^{Y_2} - \nu^{Y_2}_0)) \Big) }{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2 } \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} }{\Pr(S=1)} \cdot \frac{ 2 \Big(g_0 + r(g-g_0) \Big) \Big( (\mu^{Y_2}_0 + r(\mu^{Y_2} - \mu^{Y_2}_0)) - (\nu^{Y_2}_0 + r(\nu^{Y_2} - \nu^{Y_2}_0)) \Big) (p^{d_1} -p^{d_1}_0)^2 }{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^3 } \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} I \{D_2 = d_2 \} }{\Pr(S=1)} \cdot \frac{ (-2) (g-g_0) \Big(Y - (\mu^{Y_2}_0 + r(\mu^{Y_2}-\mu^{Y_2}_0)) \Big) (p^{d_1} -p^{d_1}_0)}{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2 \left( p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right) } \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} I \{D_2 = d_2 \} }{\Pr(S=1)} \cdot \frac{ (-2) (g-g_0) \Big(Y - (\mu^{Y_2}_0 + r(\mu^{Y_2}-\mu^{Y_2}_0)) \Big) (p^{d_2} -p^{d_2}_0)}{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right) \left( p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)^2 } \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} I \{D_2 = d_2 \} }{\Pr(S=1)} \cdot \frac{ (-2) (g-g_0) (\mu^{Y_2}-\mu^{Y_2}_0) }{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right) \left( p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right) } \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} I \{D_2 = d_2 \} }{\Pr(S=1)} \cdot \frac{ 2 \Big(g_0 + r(g-g_0) \Big) \Big(Y - (\mu^{Y_2}_0 + r(\mu^{Y_2}-\mu^{Y_2}_0)) \Big) (p^{d_1} -p^{d_1}_0)^2}{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^3 \left( p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right) } \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} I \{D_2 = d_2 \} }{\Pr(S=1)} \cdot \frac{ 2 \Big(g_0 + r(g-g_0) \Big) \Big(Y - (\mu^{Y_2}_0 + r(\mu^{Y_2}-\mu^{Y_2}_0)) \Big) (p^{d_2} -p^{d_2}_0)^2}{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right) \left( p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)^3 } \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} I \{D_2 = d_2 \} }{\Pr(S=1)} \cdot \frac{ 2 \Big(g_0 + r(g-g_0) \Big) \Big(Y - (\mu^{Y_2}_0 + r(\mu^{Y_2}-\mu^{Y_2}_0)) \Big) (p^{d_1} -p^{d_1}_0)(p^{d_2} -p^{d_2}_0)}{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2 \left( p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)^2 } \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} I \{D_2 = d_2 \} }{\Pr(S=1)} \cdot \frac{ 2 \Big(g_0 + r(g-g_0) \Big) (\mu^{Y_2} - \mu^{Y_2}_0) (p^{d_1} -p^{d_1}_0)}{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right)^2 \left( p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right) } \Bigg] \\ \notag
&+& E\Bigg[ \frac{I \{D_1 = d_1 \} I \{D_2 = d_2 \} }{\Pr(S=1)} \cdot \frac{ 2 \Big(g_0 + r(g-g_0) \Big) (\mu^{Y_2} - \mu^{Y_2}_0) (p^{d_2} -p^{d_2}_0)}{\left( p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)\right) \left( p^{d_2}_0 + r(p^{d_2} -p^{d_2}_0)\right)^2 } \Bigg] \\ \notag
\end{eqnarray}
here we follow the same procedure as in bounding ((ref)), with the only exception that now we have to make use of the last two inequalities from the regularity conditions ((ref)).
As an example, consider the first term:
\begin{eqnarray*}
\left| E\Bigg[ \frac{I \{D_1 = d_1 \} }{\Pr(S=1)} \cdot \frac{ 2 (g-g_0) \Big( (\mu^{Y_2} - \mu^{Y_2}_0) - (\nu^{Y_2} - \nu^{Y_2}_0) \Big) }{p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)} \Bigg] \right| &\leq& \left|E\Bigg[ \frac{I \{D_1 = d_1 \} }{\Pr(S=1)} \cdot \frac{ 2 (g-g_0) (\mu^{Y_2} - \mu^{Y_2}_0) }{p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)} \Bigg] \right| \\
&+& \left|E\Bigg[ \frac{I \{D_1 = d_1 \} }{\Pr(S=1)} \cdot \frac{ 2 (g-g_0) (\nu^{Y_2} - \nu^{Y_2}_0) }{p^{d_1}_0 + r(p^{d_1} -p^{d_1}_0)}\Bigg] \right| \notag \\
&\leq& \frac{2}{\epsilon^2} \frac{\delta^_N}{\epsilon} n^{-1/2} + \frac{2}{\epsilon^2} \frac{\delta^_N}{\epsilon} n^{-1/2} = 4 \frac{\delta^_N}{\epsilon^{3}} n^{-1/2}. \notag
\end{eqnarray*}
We may bound all the remaining terms similarly and get that for some constant $C_{\epsilon}''$ that only depends on $C$ and $\epsilon$
\begin{equation}
\left|\frac{\partial^2 f(r)}{\partial r^2} \right| \leq C_{\epsilon}” \delta_n n^{-1/2} \leq \delta_n' n^{-1/2} \notag
\end{equation}
and this gives the upper bound on $\lambda'_n$ in Assumption 3.2(c) of Chetal2018 as long as $C_{\epsilon} \geq C_{\epsilon}''$.
\textbf{Assumption 3.2(d)}
\begin{eqnarray}
E\Big[ (\psi^{\underline{d}_2,S=1}(W, \chi_0, \Psi_{0}^{\underline{d}_2,S=1}) )^2\Big] &=& E\Bigg[ \Bigg( \underbrace{ \frac{g(X_0)}{\Pr(S=1)} \cdot \frac{ I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} }_{=I_1} \notag\\
& + & \underbrace{ \frac{g(X_0)}{\Pr(S=1)} \cdot\frac{I\{D_1=d_1\}\cdot [\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}{p_0^{d_1}(X_0)} }_{=I_2} \notag\\
& + & \underbrace{ \frac{S}{\Pr(S=1)} \cdot \nu_0^{Y_2}(\underline{d}_2,X_0) - \Psi^{\underline{d}_2}_{0}}_{=I_3} \Bigg)^2 \Bigg] \notag\\
& = & E[I_1^2 + I_2^2 + I_3^2] \geq E[I^2_1]\notag\\
& = & E\Bigg[ \frac{g(X_0)}{\Pr(S=1)} \cdot I\{D_1=d_1\} \cdot I\{D_2=d_2\} \cdot \Bigg( \frac{ [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \Bigg)^2 \Bigg] \notag\\
& \geq & \frac{ \epsilon^3}{1-\epsilon} E\Bigg[ \Bigg( \frac{ [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}{p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \Bigg)^2 \Bigg] \notag\\
&\geq& \frac{\epsilon^3 c^2}{(1-\epsilon)^5} > 0. \notag
\end{eqnarray}
because $\Pr(\underline{D}_2 = \underline{d}_2|\underline{X}_1)= p_0^{d_1} (X_0) \cdot p_0^{d_2} (d_1,\underline{X}_1) \geq \epsilon^2$, $p_0^{d_2}(d_1,\underline{X}_1) \leq 1-\epsilon$ and $g(X_0) \geq \epsilon.$
where the second equality follows from
\begin{eqnarray}
E\Big[ I_1 \cdot I_2\Big] &=& E\Bigg[ \left( \frac{g(X_0)}{\Pr(S=1)} \right)^2 \cdot \overbrace{\frac{ I\{D_1=d_1\} \cdot I\{D_2=d_2\}}{ (p_0^{d_1}(X_0))^2\cdot p_0^{d_2}(d_1,\underline{X}_1)} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}^{E[\cdot|X_0]=E[E[Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)|\underline{D}_2=\underline{d}_2,\underline{X}_1]|D_1=d_1,X_0]=0} \cdot [\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)] \Bigg], \notag\\
E\Big[ I_2 \cdot I_3\Big] &=& E\Bigg[ \frac{g(X_0) \cdot S}{\left( \Pr(S=1) \right)^2} \cdot \overbrace{ \frac{ I\{D_1=d_1\}}{p_0^{d_1}(X_0)} \cdot [\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)-\nu_0^{Y_2}(\underline{d}_2,X_0)]}^{E[\cdot|X_0]=\int E\big[ \mu_0^{Y_2}(\underline{d}_2,\underline{x}_1)-\nu_0^{Y_2}(\underline{d}_2,x_0) \big| D_1=d_1, \underline{X}_1=\underline{x}_1 \big] dF_{X_1=x_1|D_1=d_1,X_0=x_0}=0} \cdot [ \nu_0^{Y_2}(\underline{d}_2,X_0) - \Psi^{\underline{d}_2}_{0}] \Bigg],\notag\\
E\Big[ I_1 \cdot I_3\Big] &=& E\Bigg[ \frac{g(X_0) \cdot S}{\left( \Pr(S=1) \right)^2} \cdot \overbrace{\frac{ I\{D_1=d_1\} \cdot I\{D_2=d_2\}}{ p_0^{d_1}(X_0)\cdot p_0^{d_2}(d_1,\underline{X}_1)} \cdot [Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)]}^{E[\cdot|X_0]=E[E[Y_2-\mu_0^{Y_2}(\underline{d}_2,\underline{X}_1)|\underline{D}_2=\underline{d}_2,\underline{X}_1]|D_1=d_1,X_0]=0} \cdot [\nu_0^{Y_2}(\underline{d}_2,X_0) - \Psi^{\underline{d}_2}_{0}] \Bigg]. \notag
\end{eqnarray}
}
\section{Covariates}
Table (ref) provides information on the covariates in our empirical application across treatment sequences. The first two columns contain the name and a description of each variable. The variable type in the third column can take the value 1, 2, or 3, which stands for dummy, categorical, or continuous variable, respectively. The fourth column presents an indicator which is 0 for covariates observed prior to the first treatment ($X_0$) and 1 for covariates observed after the first treatment ($X_1$). The number of missing values is given in the fifth column, and columns 6-15 display the mean values of the covariates for the treatment sequences in Table (ref).
\begin{landscape}
\tiny
\begin{longtable}{ll|rrr|rrrrrrrrrrr}
\caption[Description of regressors and means across treatment sequences]{Description of regressors and means across treatment sequences}
\\
\hline \multicolumn{2}{c}{{Variable description}} & \multicolumn{3}{c}{{Statistics}} & \multicolumn{11}{c}{{Mean values across treatment sequences}} \\
\hline name & description & type & x & miss & -1 & 00 & 11 & 12 & 13 & 21 & 22 & 23 & 31 & 32 & 33 \\ \hline
\endfirsthead
\multicolumn{16}{c}
{{ \tablename\ \Alph{section}.\arabic{table} -- continued from previous page}} \\
\hline name & description & type & x & miss & -1 & 00 & 11 & 12 & 13 & 21 & 22 & 23 & 31 & 32 & 33 \\ \hline
\endhead
\hline \multicolumn{16}{c}{{Continued on next page}} \\ \hline
\endfoot
jcmsa & MSA CATEGORY & 2 & 0 & 219 & 1.88 & 1.91 & 1.98 & 2.09 & 1.95 & 1.86 & 1.86 & 1.77 & 1.95 & 1.86 & 1.90 \\
age & AGE IN YEARS AT BASELINE & 3 & 0 & 219 & 19.08 & 18.78 & 19.04 & 18.44 & 18.98 & 18.46 & 18.54 & 18.79 & 19.01 & 18.55 & 19.32 \\
RACE_ETH & RACE OR ETHNICITY & 2 & 0 & 222 & 2.04 & 2.05 & 2.00 & 2.05 & 2.05 & 2.10 & 2.22 & 2.30 & 1.96 & 2.15 & 2.02 \\
NTV_LANG & NATIVE LANGUAGE & 2 & 0 & 236 & 1.18 & 1.18 & 1.19 & 1.09 & 1.20 & 1.17 & 1.33 & 1.37 & 1.14 & 1.32 & 1.20 \\
HH14 & HEAD OF HOUSE WHEN SAMPLE MEMBER WAS 14 & 2 & 0 & 306 & 2.46 & 2.43 & 2.37 & 2.37 & 2.39 & 2.56 & 2.41 & 2.45 & 2.36 & 2.37 & 2.31 \\
WELF_KID & FAMILY ON WELFARE WHEN GROWING UP & 2 & 0 & 905 & 2.10 & 2.08 & 2.08 & 2.40 & 2.08 & 2.15 & 2.08 & 2.02 & 1.98 & 2.41 & 1.93 \\
HGC_MOTH & HIGHEST GRADE MOTHER COMPLETED & 3 & 0 & 2243 & 11.47 & 11.55 & 11.29 & 10.92 & 11.39 & 11.60 & 10.53 & 10.88 & 11.75 & 10.89 & 11.53 \\
M_WORK14 & MOTHER WORKED WHEN SAMPLE MEMBER WAS 14 & 1 & 0 & 1805 & 0.72 & 0.74 & 0.70 & 0.61 & 0.81 & 0.77 & 0.70 & 0.68 & 0.74 & 0.73 & 0.70 \\
OCC_MOTH & OCCUPATION OF MOTHER WHEN SAMPLE WAS 14 & 2 & 0 & 4351 & 2.80 & 2.82 & 2.86 & 2.65 & 2.45 & 2.89 & 3.11 & 3.22 & 2.88 & 2.75 & 2.91 \\
HGC_FATH & HIGHEST GRADE FATHER COMPLETED & 3 & 0 & 4462 & 11.36 & 11.55 & 11.46 & 10.90 & 11.20 & 11.41 & 10.65 & 11.04 & 11.71 & 10.83 & 11.64 \\
F_WORK14 & FATHER WORKED WHEN SAMPLE MEMBER WAS 14 & 1 & 0 & 4090 & 0.89 & 0.91 & 0.91 & 0.80 & 0.90 & 0.89 & 0.91 & 0.91 & 0.87 & 0.94 & 0.93 \\
OCC_FATH & OCCUPATION OF FATHER WHEN SAMPLE WAS 14 & 2 & 0 & 4845 & 3.51 & 3.59 & 3.58 & 2.50 & 3.37 & 3.33 & 3.49 & 3.30 & 3.47 & 3.69 & 3.48 \\
marriage & marital status & 2 & 0 & 226 & 1.23 & 1.16 & 1.17 & 1.19 & 1.32 & 1.16 & 1.10 & 1.11 & 1.18 & 1.06 & 1.13 \\
haschld & had children at random assignment & 1 & 0 & 291 & 0.23 & 0.18 & 0.22 & 0.40 & 0.32 & 0.19 & 0.18 & 0.12 & 0.20 & 0.15 & 0.16 \\
proplive & PROPORTION OF CHILDREN WHO LIVE WITH & 2 & 0 & 9139 & 1.53 & 1.61 & 1.37 & 1.12 & 1.77 & 1.60 & 1.47 & 1.77 & 1.77 & 1.44 & 1.49 \\
PREGN_RA & CURRENTLY PREGNANT & 2 & 0 & 6619 & 1.98 & 1.99 & 2.01 & 1.93 & 2.00 & 2.01 & 2.00 & 2.04 & 1.99 & 2.00 & 2.00 \\
old & AGE OF OLDEST CHILD & 3 & 0 & 9147 & 2.20 & 1.91 & 2.04 & 1.88 & 1.85 & 1.79 & 1.68 & 2.09 & 1.90 & 2.06 & 2.11 \\
yng & AGE OF YOUNGEST CHILD & 3 & 0 & 9143 & 1.33 & 1.17 & 1.39 & 1.29 & 1.38 & 1.10 & 0.88 & 0.95 & 1.24 & 1.00 & 1.17 \\
othwith & PLACE WHERE ABSENT CHILDREN LIVE & 2 & 0 & 10655 & 1.47 & 1.40 & 1.36 & 1.00 & 1.20 & 1.34 & 1.14 & 1.00 & 1.37 & 2.75 & 1.44 \\
nchld & number of children & 3 & 0 & 9139 & 1.51 & 1.41 & 1.39 & 1.29 & 1.31 & 1.41 & 1.39 & 1.41 & 1.38 & 1.50 & 1.48 \\
ageparnt & AGE WHEN SAMPLE MEMBER BECAME A PARENT & 3 & 0 & 9154 & 18.25 & 18.25 & 18.42 & 17.56 & 17.66 & 18.10 & 18.12 & 17.41 & 18.51 & 17.81 & 18.41 \\
NUMB_HH & NUMBER IN HOUSEHOLD & 3 & 0 & 262 & 4.49 & 4.47 & 4.26 & 4.44 & 4.88 & 4.59 & 4.72 & 4.58 & 4.39 & 4.82 & 4.47 \\
R_HEAD & SAMPLE MEMBER IS HEAD OF HOUSEHOLD & 1 & 0 & 262 & 0.15 & 0.12 & 0.15 & 0.21 & 0.10 & 0.10 & 0.10 & 0.09 & 0.12 & 0.12 & 0.10 \\
hhmemb & HOUSEHOLD MEMBERSHIP & 2 & 0 & 262 & 3.18 & 2.89 & 3.02 & 3.19 & 3.28 & 2.85 & 2.73 & 2.86 & 2.94 & 2.84 & 2.91 \\
HOUS_ARR & CURRENT HOUSING ARRANGEMENT & 2 & 0 & 371 & 2.30 & 2.29 & 2.25 & 2.10 & 2.55 & 2.23 & 2.23 & 2.28 & 2.24 & 2.20 & 2.31 \\
PAY_RENT & SAMPLE MEMBER CONTRIBUTES TO RENT & 1 & 0 & 717 & 0.29 & 0.26 & 0.28 & 0.45 & 0.29 & 0.22 & 0.20 & 0.22 & 0.25 & 0.22 & 0.26 \\
hgc & highest grade completed & 3 & 0 & 238 & 10.17 & 10.07 & 10.25 & 9.70 & 10.32 & 9.75 & 9.70 & 9.83 & 10.33 & 9.94 & 10.46 \\
HS_D & HAD HS DIPLOMA AT RANDOM ASSIGNMENT & 1 & 0 & 268 & 0.20 & 0.18 & 0.24 & 0.05 & 0.27 & 0.09 & 0.09 & 0.18 & 0.25 & 0.14 & 0.33 \\
GED_D & HAD GED AT RANDOM ASSIGNMENT & 1 & 0 & 228 & 0.05 & 0.05 & 0.06 & 0.00 & 0.07 & 0.02 & 0.01 & 0.01 & 0.07 & 0.03 & 0.05 \\
VOC_D & HAD VOC DEGREE AT RANDOM ASSIGNMENT & 1 & 0 & 249 & 0.02 & 0.02 & 0.03 & 0.02 & 0.02 & 0.02 & 0.02 & 0.02 & 0.02 & 0.02 & 0.02 \\
OTH_DEG & HAD OTHER DEGREE AT RANDOM ASSIGNMENT & 1 & 0 & 225 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.01 & 0.00 & 0.01 & 0.00 & 0.01 \\
inschool & IN SCHOOL MONTH PRIOR TO JC APPLICATION & 1 & 0 & 421 & 0.22 & 0.26 & 0.27 & 0.20 & 0.29 & 0.27 & 0.31 & 0.31 & 0.23 & 0.30 & 0.25 \\
ANY_ED1 & ATTENDED ANY ED OR TRG IN PAST YEAR & 1 & 0 & 229 & 0.63 & 0.67 & 0.66 & 0.56 & 0.66 & 0.71 & 0.71 & 0.68 & 0.66 & 0.76 & 0.65 \\
N_ED_CAT & NUMBER OF ED PROGRAMS IN PAST YEAR & 2 & 0 & 4039 & 1.30 & 1.33 & 1.27 & 1.36 & 1.33 & 1.32 & 1.31 & 1.31 & 1.31 & 1.32 & 1.25 \\
monined & MOTHERS IN ED PROGRAMS IN PAST YEAR & 3 & 0 & 4429 & 6.40 & 6.94 & 7.00 & 7.18 & 7.14 & 7.03 & 7.38 & 7.10 & 6.65 & 7.06 & 7.05 \\
reasleft & MAIN REASON LEFT SCHOOL & 2 & 0 & 7644 & 4.10 & 4.03 & 3.99 & 4.89 & 3.86 & 4.36 & 4.78 & 4.04 & 3.87 & 3.44 & 4.29 \\
REC_ED & MOST RECENT EDUCATION OR TRAINING PROGRAM & 2 & 0 & 4073 & 1.35 & 1.26 & 1.33 & 1.23 & 1.00 & 1.21 & 1.26 & 1.16 & 1.31 & 1.42 & 1.26 \\
TYPEED_R & TYPE OF MOST RECENT ED PROGRAM & 2 & 0 & 4086 & 3.04 & 2.85 & 3.22 & 3.14 & 2.81 & 2.71 & 2.83 & 2.88 & 2.97 & 3.09 & 2.99 \\
NHRSED_R & USUAL HOURS/WK IN MOST RECENT ED PROGRAM & 3 & 0 & 4161 & 26.00 & 26.94 & 25.12 & 26.23 & 28.27 & 27.04 & 27.81 & 27.06 & 25.74 & 27.77 & 27.26 \\
REASED_R & MAIN REASON LEFT MOST RECENT PROGRAM & 2 & 0 & 5904 & 4.29 & 4.19 & 4.30 & 4.62 & 4.16 & 4.53 & 4.87 & 4.50 & 4.13 & 3.82 & 3.77 \\
numbjobs & NUMBER OF JOBS IN PAST YEAR & 3 & 0 & 4212 & 1.77 & 1.74 & 1.77 & 1.58 & 1.90 & 1.72 & 1.49 & 1.69 & 1.81 & 1.76 & 1.82 \\
evworkb & EVER HAD FULL OR PART TIME JOB & 1 & 0 & 221 & 0.81 & 0.79 & 0.79 & 0.81 & 0.93 & 0.76 & 0.70 & 0.73 & 0.85 & 0.69 & 0.79 \\
YR_WORK1 & HAD JOB IN PAST YEAR & 1 & 0 & 220 & 0.66 & 0.64 & 0.67 & 0.58 & 0.71 & 0.61 & 0.53 & 0.58 & 0.70 & 0.55 & 0.63 \\
EARN_YR & EARNINGS IN PAST YEAR & 3 & 0 & 969 & 3116.56 & 2867.37 & 3062.45 & 2494.66 & 2656.12 & 2325.72 & 3276.94 & 2054.90 & 3338.08 & 2247.93 & 2845.55 \\
mosinjob & months employed in past year & 3 & 0 & 4691 & 6.08 & 6.04 & 6.68 & 5.48 & 6.03 & 5.72 & 6.07 & 5.26 & 6.11 & 5.98 & 6.56 \\
REC_JOB & MOST RECENT JOB & 2 & 0 & 4362 & 1.14 & 1.13 & 1.13 & 1.28 & 1.03 & 1.13 & 1.16 & 1.09 & 1.15 & 1.10 & 1.15 \\
OCC_R & OCCUPATION AT MOST RECENT JOB & 2 & 0 & 4389 & 3.12 & 2.95 & 3.08 & 3.48 & 3.14 & 3.06 & 3.04 & 2.54 & 3.22 & 2.71 & 3.20 \\
HRSWK_JR & USUAL WEEKLY HOURS AT MOST RECENT JOB & 3 & 0 & 4430 & 35.78 & 35.12 & 35.80 & 38.88 & 35.07 & 34.48 & 36.32 & 34.93 & 35.10 & 33.71 & 35.35 \\
hrwager & hourly wage at most recent job & 3 & 0 & 4714 & 5.13 & 5.06 & 4.87 & 4.95 & 4.41 & 4.83 & 4.88 & 4.78 & 5.10 & 4.64 & 5.11 \\
COOP_R & MOST RECENT JOB PART OF CO-OP PROGRAM & 1 & 0 & 4417 & 0.05 & 0.06 & 0.04 & 0.00 & 0.04 & 0.06 & 0.07 & 0.08 & 0.04 & 0.05 & 0.05 \\
GOVPRG_R & MOST RECENT JOB PART OF GOVT PROGRAM & 1 & 0 & 4499 & 0.06 & 0.07 & 0.03 & 0.00 & 0.14 & 0.07 & 0.06 & 0.09 & 0.05 & 0.07 & 0.05 \\
leftjobr & LEFT MOST RECENT JOB PRIOR TO RA & 1 & 0 & 4409 & 0.67 & 0.67 & 0.61 & 0.72 & 0.76 & 0.68 & 0.63 & 0.67 & 0.68 & 0.67 & 0.65 \\
rslftjr & MAIN REASON LEFT MOST RECENT JOB & 2 & 0 & 7260 & 3.63 & 3.54 & 4.01 & 4.33 & 3.78 & 3.43 & 3.73 & 3.88 & 3.80 & 3.88 & 3.75 \\
MOS_AFDC & MOSTS RECEIVED AFDC IN PAST YEAR & 3 & 0 & 8277 & 11.04 & 11.02 & 11.31 & 11.48 & 10.40 & 11.22 & 11.63 & 10.23 & 10.99 & 11.34 & 10.96 \\
MOS_OTHW & MONTHS RECEIVED OTHER WELFARE IN PY & 3 & 0 & 8760 & 11.26 & 11.16 & 11.06 & 10.31 & 12.00 & 11.43 & 11.01 & 11.14 & 11.17 & 9.81 & 10.70 \\
MOS_FS & MONTHS RECEIVED FOOD STAMPS IN PAST YEAR & 3 & 0 & 6847 & 10.91 & 10.75 & 11.08 & 11.10 & 10.73 & 11.02 & 11.04 & 10.57 & 10.67 & 11.26 & 10.80 \\
GOT_ANYW & RECEIVED ANY PUBLIC ASSISTANCE IN PY & 1 & 0 & 1344 & 0.62 & 0.60 & 0.59 & 0.80 & 0.54 & 0.63 & 0.61 & 0.48 & 0.57 & 0.56 & 0.55 \\
MOS_ANYW & MONTHS RECEIVED ANY PUBLIC ASSIST IN PY & 3 & 0 & 5463 & 11.20 & 11.14 & 11.34 & 11.84 & 10.75 & 11.34 & 11.46 & 10.92 & 11.12 & 11.21 & 10.97 \\
GOTAFDC1 & RECEIVED AFDC IN PAST YEAR & 1 & 0 & 977 & 0.35 & 0.32 & 0.34 & 0.52 & 0.32 & 0.36 & 0.35 & 0.21 & 0.33 & 0.37 & 0.29 \\
GOTOTHW1 & RECEIVED OTHER WELFARE IN PAST YEAR & 1 & 0 & 999 & 0.28 & 0.28 & 0.23 & 0.32 & 0.18 & 0.30 & 0.26 & 0.20 & 0.26 & 0.21 & 0.24 \\
GOTFS1 & RECEIVED FOOD STAMPS IN PAST YEAR & 1 & 0 & 554 & 0.48 & 0.45 & 0.49 & 0.71 & 0.41 & 0.48 & 0.48 & 0.38 & 0.43 & 0.45 & 0.39 \\
HH_INC & TOTAL HOUSEHOLD INCOME & 2 & 0 & 4210 & 2.81 & 2.89 & 2.83 & 2.39 & 2.88 & 2.75 & 2.67 & 2.75 & 3.16 & 2.61 & 3.05 \\
PERS_INC & TOTAL PERSONAL INCOME & 2 & 0 & 978 & 1.37 & 1.32 & 1.28 & 1.26 & 1.33 & 1.25 & 1.19 & 1.28 & 1.39 & 1.19 & 1.38 \\
health & HEALTH STATUS & 1 & 0 & 231 & 1.68 & 1.68 & 1.64 & 1.77 & 1.63 & 1.69 & 1.72 & 1.61 & 1.66 & 1.61 & 1.64 \\
sick & HAD HEALTH PROBLEM THAT LIMITED WORK & 1 & 0 & 230 & 0.05 & 0.05 & 0.06 & 0.05 & 0.02 & 0.04 & 0.03 & 0.04 & 0.05 & 0.03 & 0.04 \\
typehlth & TYPE HEALTH PROBLEM THAT LIMITED WORK & 2 & 0 & 10774 & 3.64 & 3.76 & 3.25 & 1.50 & 8.00 & 3.25 & 3.78 & 4.29 & 3.43 & 2.33 & 2.95 \\
timesick & TIME HAD HEALTH PROBLEM THAT LIMITED WORK & 3 & 0 & 10790 & 8.12 & 9.49 & 9.86 & 18.00 & 18.00 & 7.84 & 8.67 & 3.24 & 8.18 & 9.50 & 9.06 \\
EV_CIG & EVER SMOKED CIGARETTES & 1 & 0 & 221 & 0.53 & 0.54 & 0.55 & 0.56 & 0.54 & 0.54 & 0.44 & 0.44 & 0.57 & 0.45 & 0.48 \\
PY_CIG & SMOKED CIGARETTES IN PAST YEAR & 1 & 0 & 230 & 0.51 & 0.52 & 0.53 & 0.53 & 0.54 & 0.52 & 0.43 & 0.42 & 0.55 & 0.41 & 0.47 \\
EV_ALCHL & EVER DRANK ALCOHOL & 1 & 0 & 222 & 0.59 & 0.58 & 0.64 & 0.51 & 0.68 & 0.56 & 0.47 & 0.45 & 0.65 & 0.49 & 0.59 \\
PY_ALCHL & DRANK ALCOHOL IN PAST YEAR & 1 & 0 & 242 & 0.54 & 0.53 & 0.56 & 0.42 & 0.61 & 0.51 & 0.42 & 0.41 & 0.60 & 0.47 & 0.54 \\
EV_POT & EVER SMOKED MARIJUANA & 1 & 0 & 232 & 0.36 & 0.37 & 0.35 & 0.23 & 0.37 & 0.40 & 0.30 & 0.34 & 0.40 & 0.26 & 0.33 \\
PY_POT & SMOKED MARIJUANA IN PAST YEAR & 1 & 0 & 240 & 0.30 & 0.30 & 0.28 & 0.19 & 0.29 & 0.33 & 0.25 & 0.30 & 0.31 & 0.19 & 0.28 \\
EV_COKE & EVER SNORTED COCAINE & 1 & 0 & 227 & 0.04 & 0.03 & 0.04 & 0.07 & 0.02 & 0.03 & 0.01 & 0.02 & 0.04 & 0.01 & 0.03 \\
PY_COKE & SNORTED COCAINE IN PAST YEAR & 1 & 0 & 228 & 0.02 & 0.02 & 0.02 & 0.05 & 0.02 & 0.02 & 0.01 & 0.01 & 0.03 & 0.00 & 0.02 \\
EV_CRACK & EVER SMOKED CRACK & 1 & 0 & 225 & 0.02 & 0.02 & 0.01 & 0.05 & 0.02 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
PY_CRACK & SMOKED CRACK IN PAST YEAR & 1 & 0 & 226 & 0.01 & 0.01 & 0.01 & 0.02 & 0.02 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.01 \\
EV_HROIN & EVER USED HEROIN & 1 & 0 & 223 & 0.02 & 0.01 & 0.01 & 0.05 & 0.02 & 0.01 & 0.00 & 0.01 & 0.01 & 0.00 & 0.00 \\
PY_HROIN & USED HEROIN IN PAST YEAR & 1 & 0 & 223 & 0.01 & 0.01 & 0.01 & 0.05 & 0.02 & 0.01 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 \\
EV_SPEED & EVER USED SPEED & 1 & 0 & 226 & 0.05 & 0.04 & 0.05 & 0.07 & 0.02 & 0.03 & 0.03 & 0.03 & 0.07 & 0.01 & 0.04 \\
PY_SPEED & USED SPEED IN PAST YEAR & 1 & 0 & 228 & 0.03 & 0.03 & 0.05 & 0.05 & 0.02 & 0.03 & 0.02 & 0.02 & 0.05 & 0.01 & 0.03 \\
EV_LSD & EVER USED LSD & 1 & 0 & 225 & 0.06 & 0.05 & 0.05 & 0.07 & 0.02 & 0.05 & 0.02 & 0.04 & 0.07 & 0.04 & 0.05 \\
PY_LSD & USED LSD IN PAST YEAR & 1 & 0 & 228 & 0.04 & 0.04 & 0.03 & 0.05 & 0.02 & 0.03 & 0.02 & 0.03 & 0.06 & 0.03 & 0.02 \\
EV_OTHDR & EVER USED OTHER ILLEGAL DRUGS & 1 & 0 & 3842 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.02 & 0.01 & 0.00 & 0.01 \\
PY_OTHDR & USED OTHER ILLEGAL DRUGS IN PAST YEAR & 1 & 0 & 3844 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.02 & 0.01 & 0.00 & 0.01 \\
EV_INJCT & EVER INJECTED DRUGS WITH NEEDLE & 1 & 0 & 224 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.01 & 0.01 & 0.00 & 0.00 \\
DRUG_TRT & EVER IN DRUG OR ALCOHOL TREATMENT & 1 & 0 & 4218 & 0.08 & 0.08 & 0.06 & 0.12 & 0.07 & 0.07 & 0.06 & 0.08 & 0.07 & 0.02 & 0.06 \\
MOUT_TRT & MONTHS PRIOR TO RA IN DRUG TREATMENT & 3 & 0 & 10904 & 17.72 & 14.94 & 16.20 & 28.80 & 33.62 & 14.80 & 4.96 & 11.76 & 20.57 & 43.29 & 11.47 \\
MOS_TRTR & MONTHS IN MOST RECENT DRUG TREATMENT & 2 & 0 & 10803 & 2.56 & 2.61 & 2.82 & 1.50 & 2.50 & 2.64 & 2.50 & 2.83 & 2.76 & 1.00 & 2.25 \\
FRQ_CIG & HOW OFTEN SMOKED CIGARETTES IN PAST YEAR & 2 & 0 & 5597 & 1.49 & 1.61 & 1.68 & 2.00 & 1.55 & 1.56 & 1.71 & 1.78 & 1.53 & 1.77 & 1.63 \\
FRQ_ALC & HOW OFTEN DRANK ALCOHOL IN PAST YEAR & 2 & 0 & 5411 & 3.37 & 3.42 & 3.41 & 3.56 & 3.12 & 3.42 & 3.36 & 3.51 & 3.47 & 3.65 & 3.50 \\
FRQ_POT & HOW OFTEN SMOKED MARIJUANA IN PAST YEAR & 2 & 0 & 8006 & 3.05 & 3.14 & 3.09 & 2.62 & 3.17 & 3.04 & 3.00 & 3.17 & 3.24 & 3.05 & 3.32 \\
FRQ_COKE & HOW OFTEN SNORTED COCAINE IN PAST YEAR & 2 & 0 & 11099 & 3.48 & 3.44 & 3.86 & 3.00 & 4.00 & 3.27 & 3.33 & 4.00 & 3.44 & NaN & 3.62 \\
FRQ_CRAC & HOW OFTEN SMOKED CRACK IN PAST YEAR & 2 & 0 & 11196 & 3.57 & 3.49 & 4.00 & 2.00 & 4.00 & 3.38 & 4.00 & 4.00 & 3.06 & NaN & 3.57 \\
FRQ_HERN & HOW OFTEN USED HEROIN IN PAST YEAR & 2 & 0 & 11220 & 3.91 & 3.43 & 3.33 & 2.50 & 3.00 & 3.17 & 4.00 & NaN & 3.62 & NaN & 4.00 \\
FRQ_SPED & HOW OFTEN USED SPEED IN PAST YEAR & 2 & 0 & 10950 & 3.39 & 3.27 & 3.41 & 3.00 & 2.00 & 3.33 & 3.86 & 4.00 & 3.38 & 4.00 & 3.38 \\
FRQ_LSD & HOW OFTEN USED LSD IN PAST YEAR & 2 & 0 & 10896 & 3.78 & 3.60 & 3.82 & 3.00 & 3.00 & 3.60 & 3.67 & 3.40 & 3.79 & 4.00 & 3.69 \\
FRQ_INJ & HOW OFTEN INJECTED DRUGS IN PAST YEAR & 2 & 0 & 11285 & 3.50 & 3.42 & 2.50 & NaN & NaN & 3.25 & 4.00 & NaN & 3.25 & NaN & 4.00 \\
FRQ_OTH & HOW OFTEN USED OTHER ILLEGAL DRUGS IN PY & 2 & 0 & 11261 & 2.80 & 3.33 & 3.50 & NaN & NaN & 4.00 & NaN & 4.00 & 3.80 & NaN & 2.50 \\
narrcat & NUMBER OF ARRESTS & 2 & 0 & 8761 & 1.68 & 1.63 & 1.54 & 1.55 & 1.58 & 1.60 & 1.60 & 1.30 & 1.70 & 1.33 & 1.49 \\
EVARRST1 & EVER ARRESTED & 1 & 0 & 224 & 0.27 & 0.27 & 0.22 & 0.30 & 0.32 & 0.28 & 0.20 & 0.21 & 0.26 & 0.17 & 0.18 \\
RC_ARRST & MOST RECENT ARREST & 2 & 0 & 8761 & 1.11 & 1.09 & 1.12 & 1.27 & 1.00 & 1.10 & 1.23 & 1.06 & 1.08 & 1.00 & 1.02 \\
MARRCAT1 & MONTHS SINCE MOST RECENT ARREST & 2 & 0 & 8761 & 1.78 & 1.78 & 1.93 & 1.45 & 1.75 & 1.81 & 1.73 & 1.73 & 1.84 & 1.89 & 1.65 \\
agearcat & AGE AT FIRST ARREST & 2 & 0 & 8761 & 1.96 & 1.88 & 1.82 & 2.09 & 2.17 & 1.77 & 1.69 & 1.85 & 1.90 & 1.50 & 1.92 \\
burglary & EVER ARRESTED FOR BURGLARY & 1 & 0 & 603 & 0.02 & 0.02 & 0.01 & 0.00 & 0.08 & 0.02 & 0.02 & 0.01 & 0.03 & 0.03 & 0.02 \\
robbery & EVER ARRESTED FOR ROBBERY & 1 & 0 & 617 & 0.01 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.01 & 0.00 \\
assault & EVER ARRESTED FOR MURDER OR ASSAULT & 1 & 0 & 603 & 0.03 & 0.02 & 0.02 & 0.09 & 0.00 & 0.03 & 0.04 & 0.01 & 0.03 & 0.02 & 0.01 \\
larceny & EVER ARRESTED FOR LARCENY & 1 & 0 & 545 & 0.11 & 0.09 & 0.09 & 0.10 & 0.20 & 0.09 & 0.06 & 0.09 & 0.11 & 0.09 & 0.07 \\
drugviol & EVER ARRESTED FOR DRUG VIOLATIONS & 1 & 0 & 605 & 0.03 & 0.03 & 0.00 & 0.05 & 0.00 & 0.03 & 0.02 & 0.00 & 0.03 & 0.02 & 0.01 \\
othpers & EVER ARRESTED FOR OTHER PERSONAL CRIMES & 1 & 0 & 587 & 0.05 & 0.05 & 0.02 & 0.07 & 0.05 & 0.04 & 0.03 & 0.03 & 0.04 & 0.03 & 0.02 \\
othmisc & EVER ARRESTED FOR OTHER MISC CRIMES & 1 & 0 & 491 & 0.12 & 0.13 & 0.11 & 0.05 & 0.15 & 0.13 & 0.08 & 0.08 & 0.12 & 0.04 & 0.08 \\
SERCR_S1 & MURDER OR ASSAULT WAS MOST SERIOUS CRIME & 1 & 0 & 430 & 0.02 & 0.02 & 0.02 & 0.09 & 0.00 & 0.03 & 0.04 & 0.01 & 0.03 & 0.02 & 0.01 \\
SERCR_S2 & ROBBERY WAS MOST SERIOUS CRIME & 1 & 0 & 499 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
SERCR_S3 & BURGLARY WAS MOST SERIOUS CRIME & 1 & 0 & 430 & 0.02 & 0.02 & 0.01 & 0.00 & 0.08 & 0.02 & 0.02 & 0.01 & 0.02 & 0.02 & 0.02 \\
SERCR_S4 & LARCENY WAS MOST SERIOUS CRIME & 1 & 0 & 430 & 0.09 & 0.08 & 0.08 & 0.07 & 0.18 & 0.07 & 0.05 & 0.09 & 0.09 & 0.08 & 0.06 \\
SERCR_S5 & DRUG VIOLATIONS WAS MOST SERIOUS CRIME & 1 & 0 & 430 & 0.02 & 0.02 & 0.00 & 0.00 & 0.00 & 0.02 & 0.01 & 0.00 & 0.02 & 0.02 & 0.01 \\
SERCR_S6 & OTHER PERS CRIMES WERE MOST SERIOUS CRIME & 1 & 0 & 430 & 0.03 & 0.04 & 0.02 & 0.07 & 0.00 & 0.03 & 0.02 & 0.02 & 0.02 & 0.01 & 0.02 \\
SERCR_S7 & OTHER MISC CRIMES WERE MOST SERIOUS CRIME & 1 & 0 & 430 & 0.06 & 0.07 & 0.08 & 0.05 & 0.05 & 0.08 & 0.05 & 0.07 & 0.06 & 0.01 & 0.06 \\
N_GUILTY & NUMBER OF TIMES CONVICTED & 3 & 0 & 9772 & 1.83 & 1.85 & 1.62 & 1.25 & 1.57 & 1.62 & 1.80 & 1.65 & 1.89 & 1.00 & 1.63 \\
GUILTY2 & EVER CONVICTED OR PLED GUILTY & 1 & 0 & 428 & 0.17 & 0.16 & 0.12 & 0.14 & 0.18 & 0.16 & 0.13 & 0.11 & 0.17 & 0.11 & 0.11 \\
wksjail & TOTAL WEEKS SPENT IN JAIL & 3 & 0 & 10908 & 19.63 & 23.39 & 12.96 & 2.14 & 59.49 & 11.96 & 8.20 & 3.37 & 17.79 & 23.90 & 9.47 \\
PENDING2 & HAS ARREST CHARGES PENDING & 1 & 0 & 493 & 0.02 & 0.02 & 0.01 & 0.02 & 0.02 & 0.01 & 0.02 & 0.01 & 0.02 & 0.01 & 0.01 \\
COPPLEA2 & EVER MADE A DEAL OR COPPED A PLEA & 1 & 0 & 906 & 0.04 & 0.04 & 0.02 & 0.03 & 0.05 & 0.03 & 0.03 & 0.02 & 0.04 & 0.01 & 0.02 \\
SERCR_C1 & MOST SERIOUS CONVICTION-MURDER OR ASSAULT & 1 & 0 & 2062 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.02 & 0.01 & 0.02 & 0.00 & 0.00 \\
SERCR_C2 & MOST SERIOUS CONVICTION-ROBBERY & 1 & 0 & 2118 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
SERCR_C3 & MOST SERIOUS CONVICTION-BURGLARY & 1 & 0 & 2025 & 0.01 & 0.01 & 0.00 & 0.00 & 0.08 & 0.01 & 0.01 & 0.01 & 0.02 & 0.02 & 0.00 \\
SERCR_C4 & MOST SERIOUS CONVICTION-LARCENY & 1 & 0 & 1734 & 0.05 & 0.04 & 0.04 & 0.00 & 0.06 & 0.04 & 0.02 & 0.05 & 0.05 & 0.04 & 0.03 \\
SERCR_C5 & MOST SERIOUS CONVICTION-DRUG VIOLATIONS & 1 & 0 & 2046 & 0.01 & 0.01 & 0.00 & 0.03 & 0.00 & 0.01 & 0.01 & 0.00 & 0.01 & 0.00 & 0.00 \\
SERCR_C6 & MOST SERIOUS CONVICTION-OTHER PERS CRIMES & 1 & 0 & 2030 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.01 & 0.01 & 0.03 & 0.00 \\
SERCR_C7 & MOST SERIOUS CONVICTION-OTHER MISC CRIMES & 1 & 0 & 1795 & 0.03 & 0.04 & 0.03 & 0.03 & 0.00 & 0.04 & 0.03 & 0.02 & 0.04 & 0.00 & 0.03 \\
ASSLT_C2 & EVER CONVICTED OF MURDER OR ASSAULT & 1 & 0 & 882 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.02 & 0.01 & 0.01 & 0.00 & 0.00 \\
ROB_C2 & EVER CONVICTED OF ROBBERY & 1 & 0 & 882 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
BURGL_C2 & EVER CONVICTED OF BURGLARY & 1 & 0 & 881 & 0.01 & 0.01 & 0.00 & 0.00 & 0.08 & 0.01 & 0.02 & 0.01 & 0.02 & 0.02 & 0.00 \\
LARCNYC2 & EVER CONVICTED OF LARCENY & 1 & 0 & 877 & 0.06 & 0.04 & 0.04 & 0.00 & 0.05 & 0.04 & 0.02 & 0.05 & 0.05 & 0.04 & 0.03 \\
DRVIOLC2 & EVER CONVICTED OF DRUG VIOLATIONS & 1 & 0 & 882 & 0.01 & 0.01 & 0.00 & 0.03 & 0.00 & 0.01 & 0.01 & 0.00 & 0.02 & 0.00 & 0.00 \\
OTHPERC2 & EVER CONVICTED OF OTHER PERS CRIMES & 1 & 0 & 882 & 0.02 & 0.02 & 0.01 & 0.00 & 0.00 & 0.01 & 0.00 & 0.01 & 0.02 & 0.03 & 0.00 \\
OTHMSCC2 & EVER CONVICTED OF OTHER MISC CRIMES & 1 & 0 & 880 & 0.05 & 0.06 & 0.05 & 0.03 & 0.00 & 0.05 & 0.04 & 0.02 & 0.05 & 0.01 & 0.04 \\
EVJAIL2 & EVER SERVED TIME IN JAIL & 1 & 0 & 858 & 0.06 & 0.06 & 0.05 & 0.03 & 0.08 & 0.06 & 0.04 & 0.05 & 0.06 & 0.02 & 0.03 \\
PAROLE2 & EVER PUT ON PROBATION OR PAROLE & 1 & 0 & 864 & 0.09 & 0.08 & 0.07 & 0.03 & 0.15 & 0.08 & 0.07 & 0.04 & 0.09 & 0.05 & 0.05 \\
HEAR_JC & HOW FIRST HEARD ABOTU JOB CORPS & 2 & 0 & 267 & 3.31 & 3.21 & 3.36 & 3.19 & 2.90 & 3.15 & 3.27 & 3.17 & 3.29 & 3.26 & 3.20 \\
FROM_OA & FIRST HEARD ABOUT JC FROM OA COUNSELOR & 1 & 0 & 277 & 0.04 & 0.03 & 0.02 & 0.07 & 0.05 & 0.03 & 0.04 & 0.05 & 0.03 & 0.08 & 0.03 \\
KNEW_JC & KNEW SOMEONE WHO ATTENDED JOB CORPS & 1 & 0 & 303 & 0.66 & 0.67 & 0.60 & 0.79 & 0.73 & 0.73 & 0.71 & 0.62 & 0.66 & 0.69 & 0.66 \\
INFO_JC & HOW GOT MOST INFO ABOUT WHAT JC IS LIKE & 2 & 0 & 482 & 3.86 & 3.75 & 4.07 & 3.69 & 3.78 & 3.62 & 3.91 & 3.66 & 3.78 & 3.50 & 3.82 \\
R_HOME & JOINED JC TO GET AWAY FROM HOME & 1 & 0 & 753 & 0.54 & 0.59 & 0.54 & 0.48 & 0.61 & 0.61 & 0.61 & 0.67 & 0.57 & 0.60 & 0.58 \\
R_COMM & JOINED JC TO GET AWAY FROM COMMUNITY & 1 & 0 & 675 & 0.60 & 0.60 & 0.59 & 0.64 & 0.68 & 0.69 & 0.65 & 0.66 & 0.59 & 0.64 & 0.53 \\
R_TRAIN & JOINED JC TO GET JOB TRAINING & 1 & 0 & 239 & 0.98 & 0.98 & 0.97 & 0.98 & 0.98 & 0.98 & 0.97 & 1.00 & 0.99 & 0.96 & 0.99 \\
R_CRGOAL & JOINED JC TO ACHIEVE CAREER GOAL & 1 & 0 & 253 & 0.99 & 0.99 & 1.00 & 1.00 & 1.00 & 0.99 & 0.99 & 0.99 & 0.99 & 1.00 & 0.99 \\
R_GETGED & JOINED JC TO GET A GED & 1 & 0 & 2910 & 0.96 & 0.95 & 0.95 & 0.98 & 0.96 & 0.96 & 0.96 & 0.95 & 0.95 & 0.93 & 0.94 \\
R_NOWORK & JOINED JC TO BE ABLE TO FIND WORK & 1 & 0 & 401 & 0.90 & 0.91 & 0.93 & 0.88 & 0.92 & 0.92 & 0.91 & 0.89 & 0.90 & 0.89 & 0.90 \\
R_OTHER & JOINED JC FOR OTHER IMPORTANT REASONS & 1 & 0 & 675 & 0.73 & 0.73 & 0.72 & 0.72 & 0.70 & 0.72 & 0.75 & 0.76 & 0.73 & 0.71 & 0.73 \\
mostimpr & MOST IMPORTANT REASON FOR JOINING JC & 2 & 0 & 223 & 2.82 & 2.80 & 2.80 & 2.72 & 3.29 & 2.94 & 2.87 & 2.94 & 2.71 & 2.56 & 2.62 \\
othimpr & MAIN OTHER REASONS FOR JOINING JC & 2 & 0 & 8927 & 2.70 & 2.67 & 2.12 & 1.86 & 2.17 & 2.70 & 2.43 & 3.25 & 2.43 & 2.82 & 2.80 \\
E_MATH & EXPECT JC TO IMPROVE MATH SKILLS & 1 & 0 & 358 & 0.68 & 0.68 & 0.72 & 0.81 & 0.68 & 0.75 & 0.82 & 0.81 & 0.62 & 0.70 & 0.67 \\
E_READ & EXPECT JC TO IMPROVE READING SKILLS & 1 & 0 & 292 & 0.52 & 0.53 & 0.51 & 0.67 & 0.52 & 0.60 & 0.67 & 0.66 & 0.47 & 0.68 & 0.50 \\
E_ALONG & EXPECT JC TO HELP GET ALONG WITH OTHERS & 1 & 0 & 294 & 0.56 & 0.59 & 0.58 & 0.51 & 0.65 & 0.64 & 0.69 & 0.66 & 0.60 & 0.62 & 0.60 \\
E_CONTRL & EXPECT JC TO IMPROVE SELF CONTROL & 1 & 0 & 292 & 0.54 & 0.58 & 0.51 & 0.60 & 0.63 & 0.62 & 0.68 & 0.66 & 0.56 & 0.64 & 0.56 \\
E_ESTEEM & EXPECT JC TO IMPROVE SELF ESTEEM & 1 & 0 & 300 & 0.54 & 0.57 & 0.53 & 0.63 & 0.66 & 0.62 & 0.65 & 0.70 & 0.57 & 0.66 & 0.56 \\
E_SPCJOB & EXPECT JC TO GIVE TRG FOR SPECIFIC JOB & 1 & 0 & 284 & 0.94 & 0.96 & 0.95 & 0.98 & 0.98 & 0.95 & 0.94 & 0.97 & 0.97 & 0.98 & 0.96 \\
E_FRIEND & EXPECT JC TO LEAD TO NEW FRIENDSHIPS & 1 & 0 & 305 & 0.69 & 0.69 & 0.72 & 0.60 & 0.85 & 0.71 & 0.73 & 0.72 & 0.72 & 0.71 & 0.69 \\
knewcntr & KNEW JC CENTER THAT WANTED TO ATTEND & 1 & 0 & 259 & 0.51 & 0.53 & 0.49 & 0.64 & 0.34 & 0.52 & 0.53 & 0.48 & 0.50 & 0.53 & 0.47 \\
imprcntr & MAIN REASON WANTS TO ATTEND CENTER & 2 & 0 & 5715 & 2.74 & 2.88 & 2.60 & 2.59 & 3.29 & 2.88 & 2.73 & 2.96 & 2.91 & 2.89 & 2.75 \\
knewjob & KNEW WHAT JOB WANTED TO TRAIN FOR & 1 & 0 & 257 & 0.83 & 0.86 & 0.85 & 0.79 & 0.80 & 0.85 & 0.84 & 0.86 & 0.87 & 0.81 & 0.86 \\
typejobb & TYPE OF JOB WANTED TO TRAIN FOR & 2 & 0 & 3169 & 3.99 & 4.16 & 3.78 & 3.30 & 4.50 & 3.98 & 4.33 & 3.54 & 4.08 & 3.79 & 4.00 \\
EARN_CMP & EXPECTED EARNINGS PER HR AFTER JC & 3 & 0 & 6238 & 9.96 & 10.23 & 9.79 & 8.10 & 9.38 & 10.12 & 10.76 & 8.91 & 10.07 & 10.14 & 9.48 \\
hadworry & WORRIED ABOUT ATTENDING JC & 1 & 0 & 245 & 0.34 & 0.31 & 0.34 & 0.28 & 0.39 & 0.35 & 0.39 & 0.36 & 0.37 & 0.38 & 0.39 \\
typeworr & MAIN TYPE OF WORRY ABOUT ATTENDING JC & 2 & 0 & 7557 & 3.56 & 3.53 & 3.38 & 2.42 & 3.19 & 3.50 & 3.90 & 3.77 & 3.58 & 3.59 & 3.39 \\
TALK_PAR & TALKED TO PARENTS ABOUT ATTENDING JC & 1 & 0 & 248 & 0.75 & 0.79 & 0.81 & 0.84 & 0.88 & 0.83 & 0.84 & 0.84 & 0.81 & 0.80 & 0.82 \\
IMP_PAR & PARENT ADVICE WAS IMPORTANT & 1 & 0 & 2562 & 0.80 & 0.82 & 0.82 & 0.94 & 0.86 & 0.84 & 0.87 & 0.85 & 0.78 & 0.86 & 0.78 \\
ENCR_PAR & PARENT ENCOURAGED ATTENDING JC & 1 & 0 & 4447 & 0.96 & 0.98 & 0.97 & 0.97 & 0.93 & 0.98 & 0.96 & 0.98 & 0.97 & 1.00 & 0.99 \\
TALK_REL & TALKED TO RELATIVE ABOUT ATTENDING JC & 1 & 0 & 239 & 0.54 & 0.55 & 0.60 & 0.53 & 0.73 & 0.60 & 0.61 & 0.56 & 0.55 & 0.59 & 0.55 \\
IMP_REL & RELATIVE ADVICE WAS IMPORTANT & 1 & 0 & 5167 & 0.76 & 0.79 & 0.74 & 0.83 & 0.80 & 0.82 & 0.79 & 0.89 & 0.77 & 0.77 & 0.73 \\
ENCR_REL & RELATIVE ENCOURAGED ATTENDING JC & 1 & 0 & 6640 & 0.95 & 0.96 & 0.95 & 1.00 & 1.00 & 0.98 & 0.97 & 0.97 & 0.96 & 1.00 & 0.99 \\
TALK_FRD & TALKED TO FRIENDS ABOUT ATTENDING JC & 1 & 0 & 232 & 0.70 & 0.72 & 0.75 & 0.77 & 0.71 & 0.72 & 0.69 & 0.74 & 0.77 & 0.69 & 0.75 \\
IMP_FRD & FRIENDS ADVICE WAS IMPORTANT & 1 & 0 & 3359 & 0.64 & 0.62 & 0.62 & 0.73 & 0.69 & 0.65 & 0.66 & 0.69 & 0.55 & 0.68 & 0.59 \\
ENCR_FRD & FRIENDS ENCOURAGED ATTENDING JC & 1 & 0 & 6553 & 0.90 & 0.91 & 0.93 & 0.96 & 0.80 & 0.91 & 0.93 & 0.93 & 0.94 & 0.86 & 0.93 \\
TALK_TCH & TALKED TO TEACHER ABOUT ATTENDING JC & 1 & 0 & 430 & 0.17 & 0.22 & 0.18 & 0.30 & 0.27 & 0.24 & 0.27 & 0.29 & 0.19 & 0.30 & 0.23 \\
IMP_TCH & TEACHER ADVICE WAS IMPORTANT & 1 & 0 & 9052 & 0.81 & 0.81 & 0.82 & 0.69 & 0.82 & 0.83 & 0.86 & 0.84 & 0.82 & 0.84 & 0.67 \\
ENCR_TCH & TEACHER ENCOURAGED ATTENDING JC & 1 & 0 & 9531 & 0.96 & 0.95 & 0.93 & 1.00 & 1.00 & 0.97 & 0.96 & 0.90 & 0.98 & 0.96 & 0.94 \\
TALK_CW & TALKED TO CASE WORKER ABOUT ATTENDING JC & 1 & 0 & 845 & 0.11 & 0.10 & 0.09 & 0.29 & 0.08 & 0.12 & 0.13 & 0.10 & 0.09 & 0.14 & 0.11 \\
IMP_CW & CASE WORKER ADVICE WAS IMPORTANT & 1 & 0 & 10210 & 0.76 & 0.84 & 0.78 & 0.92 & 0.67 & 0.81 & 0.77 & 0.87 & 0.67 & 0.71 & 0.80 \\
ENCR_CW & CASE WORKER ENCOURAGED ATTENDING JC & 1 & 0 & 10462 & 0.99 & 0.99 & 0.95 & 1.00 & 1.00 & 0.98 & 0.96 & 1.00 & 1.00 & 1.00 & 1.00 \\
TALK_PRO & TALKED TO PROBATION OFFICER ABOUT JC & 1 & 0 & 1186 & 0.09 & 0.08 & 0.06 & 0.10 & 0.13 & 0.09 & 0.07 & 0.06 & 0.08 & 0.11 & 0.05 \\
IMP_PRO & PROBATION OFFICER ADVICE WAS IMPORTANT & 1 & 0 & 10514 & 0.78 & 0.80 & 0.83 & 1.00 & 0.60 & 0.78 & 1.00 & 1.00 & 0.78 & 0.82 & 0.73 \\
ENCR_PRO & PROBATION OFFICER ENCOURAGED ATTENDING JC & 1 & 0 & 10688 & 0.97 & 0.99 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 0.97 & 1.00 & 0.95 \\
TALK_CHL & TALKED TO CHURCH LEADER ABOUT JC & 1 & 0 & 533 & 0.05 & 0.06 & 0.03 & 0.12 & 0.05 & 0.08 & 0.09 & 0.11 & 0.07 & 0.05 & 0.08 \\
IMP_CHL & CHURCH LEADER ADVICE WAS IMPORTANT & 1 & 0 & 10634 & 0.87 & 0.90 & 0.78 & 1.00 & 1.00 & 0.92 & 0.96 & 0.84 & 0.96 & 0.80 & 0.91 \\
ENCR_CHL & CHURCH LEADER ENCOURAGED ATTENDING JC & 1 & 0 & 10708 & 0.95 & 0.97 & 1.00 & 1.00 & 1.00 & 0.97 & 1.00 & 1.00 & 0.98 & 1.00 & 0.93 \\
TALK_ADL & TALKED TO OTHER ADULT ABOUT ATTENDING JC & 1 & 0 & 247 & 0.02 & 0.02 & 0.00 & 0.00 & 0.00 & 0.02 & 0.01 & 0.01 & 0.03 & 0.02 & 0.02 \\
IMP_ADL & OTHER ADULT ADVICE WAS IMPORTANT & 1 & 0 & 11101 & 0.71 & 0.72 & 0.00 & NaN & NaN & 0.67 & 0.75 & 0.50 & 0.79 & 1.00 & 0.64 \\
ENCR_ADL & OTHER ADULT ENCOURAGED ATTENDING JC & 1 & 0 & 11165 & 0.95 & 0.95 & NaN & NaN & NaN & 0.94 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 \\
ENCR_JCR & GOT ENCOURAGEMENT FROM OA COUNSELOR & 2 & 0 & 333 & 1.58 & 1.56 & 1.55 & 1.62 & 1.48 & 1.46 & 1.43 & 1.51 & 1.57 & 1.44 & 1.55 \\
howspoke & HOW FIRST SPOKE TO OA COUNSELOR & 1 & 0 & 237 & 0.57 & 0.59 & 0.55 & 0.49 & 0.66 & 0.60 & 0.66 & 0.65 & 0.54 & 0.65 & 0.59 \\
telemode & MODE OF TELEPHONE CONTACT WITH OA COUNS & 2 & 0 & 6766 & 1.48 & 1.49 & 1.44 & 1.25 & 1.14 & 1.45 & 1.39 & 1.39 & 1.49 & 1.39 & 1.48 \\
placeipc & PLACE OF IN-PERSON CONTACT WITH OA COUNS & 2 & 0 & 5004 & 2.39 & 2.50 & 2.51 & 2.95 & 2.58 & 2.51 & 2.29 & 2.34 & 2.45 & 2.36 & 2.40 \\
talkstay & TOLD HOW LONG EXPECTED TO STAY AT JC & 1 & 0 & 1330 & 0.81 & 0.82 & 0.83 & 0.76 & 0.69 & 0.81 & 0.78 & 0.83 & 0.84 & 0.72 & 0.84 \\
WAY_STAY & WAY THAT DISCUSSED LENGTH OF STAY AT JC & 1 & 0 & 3136 & 0.66 & 0.65 & 0.62 & 0.71 & 0.62 & 0.67 & 0.69 & 0.59 & 0.62 & 0.66 & 0.62 \\
rstaycat & MOST COMMON RANGES OF EXPECTED STAY AT JC & 2 & 0 & 8481 & 2.22 & 2.31 & 2.13 & 2.67 & 2.22 & 2.24 & 2.49 & 2.38 & 2.22 & 2.44 & 2.32 \\
tstaycat & PRECISE TIME EXPECTED TO STAY AT JC & 2 & 0 & 6019 & 3.76 & 3.95 & 3.61 & 3.23 & 3.60 & 3.94 & 4.21 & 4.28 & 3.70 & 4.65 & 3.82 \\
talkvstf & TOLD WHEN COULD FIRST VISIT FAMILY & 1 & 0 & 2078 & 0.60 & 0.62 & 0.63 & 0.44 & 0.58 & 0.62 & 0.60 & 0.74 & 0.65 & 0.65 & 0.64 \\
talktold & TOLD HOW LONG UNTIL CENTER ASSIGNMENT & 1 & 0 & 427 & 0.77 & 0.79 & 0.74 & 0.78 & 0.73 & 0.78 & 0.76 & 0.80 & 0.81 & 0.83 & 0.76 \\
tradwant & TOLD CHANCES OF GETTING DESIRED TRADE & 1 & 0 & 257 & 0.83 & 0.86 & 0.85 & 0.79 & 0.80 & 0.85 & 0.84 & 0.86 & 0.87 & 0.81 & 0.86 \\
chncetrd & CHANCES OF GETTING DESIRED TRADE & 2 & 0 & 3245 & 1.83 & 1.88 & 1.79 & 2.00 & 1.87 & 1.81 & 1.78 & 1.78 & 1.79 & 1.89 & 1.81 \\
totalhrs & TOTAL HOURS SPENT WITH OA COUNSELOR & 3 & 0 & 295 & 1.94 & 1.97 & 2.01 & 1.93 & 2.07 & 2.02 & 1.95 & 2.01 & 2.18 & 1.91 & 2.13 \\
VSTF_CAT & MONTHS UNTIL COULD FIRST VISIT FAMILY & 2 & 0 & 6811 & 2.04 & 2.05 & 1.98 & 2.08 & 2.21 & 2.01 & 1.94 & 2.19 & 2.01 & 1.98 & 2.18 \\
SCHL1 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 1 & 1 & 0 & 566 & 0.40 & 0.45 & 0.42 & 0.43 & 0.48 & 0.47 & 0.50 & 0.44 & 0.44 & 0.52 & 0.45 \\
SCHL2 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 2 & 1 & 0 & 580 & 0.40 & 0.45 & 0.42 & 0.41 & 0.48 & 0.48 & 0.50 & 0.45 & 0.44 & 0.55 & 0.45 \\
SCHL3 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 3 & 1 & 0 & 584 & 0.40 & 0.45 & 0.43 & 0.41 & 0.48 & 0.49 & 0.50 & 0.45 & 0.44 & 0.56 & 0.45 \\
SCHL4 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 4 & 1 & 0 & 582 & 0.41 & 0.45 & 0.43 & 0.41 & 0.48 & 0.49 & 0.49 & 0.45 & 0.44 & 0.56 & 0.46 \\
SCHL5 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 5 & 1 & 0 & 577 & 0.40 & 0.45 & 0.43 & 0.39 & 0.50 & 0.48 & 0.49 & 0.45 & 0.44 & 0.53 & 0.46 \\
SCHL6 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 6 & 1 & 0 & 581 & 0.40 & 0.46 & 0.43 & 0.41 & 0.50 & 0.49 & 0.49 & 0.46 & 0.44 & 0.54 & 0.45 \\
SCHL7 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 7 & 1 & 0 & 578 & 0.40 & 0.46 & 0.43 & 0.41 & 0.50 & 0.48 & 0.50 & 0.46 & 0.44 & 0.53 & 0.44 \\
SCHL8 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 8 & 1 & 0 & 576 & 0.40 & 0.46 & 0.41 & 0.41 & 0.55 & 0.48 & 0.50 & 0.45 & 0.44 & 0.53 & 0.45 \\
SCHL9 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 9 & 1 & 0 & 575 & 0.39 & 0.46 & 0.41 & 0.44 & 0.57 & 0.48 & 0.50 & 0.46 & 0.44 & 0.52 & 0.44 \\
SCHL10 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 10 & 1 & 0 & 566 & 0.39 & 0.45 & 0.40 & 0.41 & 0.57 & 0.47 & 0.49 & 0.46 & 0.44 & 0.51 & 0.43 \\
SCHL11 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 11 & 1 & 0 & 558 & 0.39 & 0.45 & 0.40 & 0.39 & 0.55 & 0.47 & 0.49 & 0.47 & 0.44 & 0.50 & 0.44 \\
SCHL12 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 12 & 1 & 0 & 554 & 0.39 & 0.45 & 0.40 & 0.39 & 0.55 & 0.47 & 0.49 & 0.45 & 0.44 & 0.51 & 0.43 \\
SCHL13 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 13 & 1 & 0 & 551 & 0.39 & 0.45 & 0.39 & 0.32 & 0.55 & 0.47 & 0.49 & 0.45 & 0.44 & 0.51 & 0.44 \\
SCHL14 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 14 & 1 & 0 & 548 & 0.39 & 0.44 & 0.39 & 0.35 & 0.55 & 0.48 & 0.47 & 0.44 & 0.44 & 0.51 & 0.43 \\
SCHL15 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 15 & 1 & 0 & 546 & 0.39 & 0.44 & 0.39 & 0.35 & 0.48 & 0.48 & 0.47 & 0.42 & 0.43 & 0.50 & 0.44 \\
SCHL16 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 16 & 1 & 0 & 538 & 0.38 & 0.44 & 0.40 & 0.32 & 0.45 & 0.48 & 0.47 & 0.44 & 0.43 & 0.50 & 0.44 \\
SCHL17 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 17 & 1 & 0 & 530 & 0.38 & 0.44 & 0.40 & 0.29 & 0.45 & 0.48 & 0.48 & 0.44 & 0.42 & 0.50 & 0.44 \\
SCHL18 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 18 & 1 & 0 & 531 & 0.38 & 0.44 & 0.40 & 0.29 & 0.45 & 0.47 & 0.47 & 0.45 & 0.42 & 0.50 & 0.43 \\
SCHL19 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 19 & 1 & 0 & 529 & 0.37 & 0.43 & 0.42 & 0.32 & 0.45 & 0.47 & 0.47 & 0.44 & 0.41 & 0.50 & 0.43 \\
SCHL20 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 20 & 1 & 0 & 526 & 0.37 & 0.43 & 0.42 & 0.32 & 0.45 & 0.46 & 0.46 & 0.43 & 0.41 & 0.50 & 0.42 \\
SCHL21 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 21 & 1 & 0 & 525 & 0.37 & 0.42 & 0.42 & 0.32 & 0.42 & 0.45 & 0.46 & 0.42 & 0.41 & 0.50 & 0.42 \\
SCHL22 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 22 & 1 & 0 & 525 & 0.36 & 0.42 & 0.43 & 0.32 & 0.38 & 0.44 & 0.44 & 0.44 & 0.41 & 0.48 & 0.42 \\
SCHL23 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 23 & 1 & 0 & 523 & 0.36 & 0.42 & 0.43 & 0.32 & 0.38 & 0.45 & 0.45 & 0.44 & 0.40 & 0.48 & 0.43 \\
SCHL24 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 24 & 1 & 0 & 520 & 0.36 & 0.42 & 0.42 & 0.32 & 0.38 & 0.44 & 0.45 & 0.43 & 0.40 & 0.48 & 0.42 \\
SCHL25 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 25 & 1 & 0 & 520 & 0.35 & 0.41 & 0.43 & 0.32 & 0.35 & 0.44 & 0.45 & 0.44 & 0.40 & 0.46 & 0.41 \\
SCHL26 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 26 & 1 & 0 & 514 & 0.35 & 0.41 & 0.43 & 0.34 & 0.35 & 0.43 & 0.44 & 0.44 & 0.40 & 0.45 & 0.41 \\
SCHL27 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 27 & 1 & 0 & 505 & 0.34 & 0.41 & 0.43 & 0.34 & 0.38 & 0.44 & 0.44 & 0.43 & 0.39 & 0.43 & 0.40 \\
SCHL28 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 28 & 1 & 0 & 502 & 0.34 & 0.40 & 0.41 & 0.37 & 0.38 & 0.43 & 0.43 & 0.43 & 0.38 & 0.42 & 0.40 \\
SCHL29 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 29 & 1 & 0 & 498 & 0.33 & 0.40 & 0.41 & 0.37 & 0.39 & 0.43 & 0.43 & 0.43 & 0.38 & 0.43 & 0.40 \\
SCHL30 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 30 & 1 & 0 & 493 & 0.33 & 0.39 & 0.39 & 0.37 & 0.39 & 0.43 & 0.43 & 0.43 & 0.38 & 0.44 & 0.40 \\
SCHL31 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 31 & 1 & 0 & 484 & 0.33 & 0.39 & 0.39 & 0.34 & 0.37 & 0.42 & 0.43 & 0.42 & 0.38 & 0.42 & 0.40 \\
SCHL32 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 32 & 1 & 0 & 478 & 0.33 & 0.38 & 0.38 & 0.32 & 0.37 & 0.41 & 0.42 & 0.41 & 0.37 & 0.41 & 0.39 \\
SCHL33 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 33 & 1 & 0 & 478 & 0.32 & 0.38 & 0.38 & 0.29 & 0.37 & 0.39 & 0.42 & 0.41 & 0.36 & 0.41 & 0.39 \\
SCHL34 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 34 & 1 & 0 & 476 & 0.31 & 0.38 & 0.37 & 0.27 & 0.37 & 0.39 & 0.42 & 0.40 & 0.36 & 0.41 & 0.38 \\
SCHL35 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 35 & 1 & 0 & 473 & 0.31 & 0.38 & 0.36 & 0.22 & 0.37 & 0.38 & 0.41 & 0.39 & 0.36 & 0.38 & 0.37 \\
SCHL36 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 36 & 1 & 0 & 471 & 0.30 & 0.37 & 0.36 & 0.20 & 0.35 & 0.38 & 0.41 & 0.40 & 0.34 & 0.37 & 0.37 \\
SCHL37 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 37 & 1 & 0 & 462 & 0.29 & 0.36 & 0.36 & 0.20 & 0.35 & 0.37 & 0.40 & 0.38 & 0.34 & 0.37 & 0.36 \\
SCHL38 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 38 & 1 & 0 & 461 & 0.28 & 0.35 & 0.35 & 0.20 & 0.35 & 0.37 & 0.40 & 0.37 & 0.33 & 0.36 & 0.36 \\
SCHL39 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 39 & 1 & 0 & 452 & 0.28 & 0.34 & 0.35 & 0.20 & 0.33 & 0.35 & 0.40 & 0.38 & 0.32 & 0.35 & 0.34 \\
SCHL40 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 40 & 1 & 0 & 453 & 0.27 & 0.33 & 0.35 & 0.20 & 0.36 & 0.34 & 0.38 & 0.38 & 0.32 & 0.34 & 0.32 \\
SCHL41 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 41 & 1 & 0 & 448 & 0.26 & 0.31 & 0.32 & 0.17 & 0.36 & 0.33 & 0.37 & 0.38 & 0.31 & 0.31 & 0.32 \\
SCHL42 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 42 & 1 & 0 & 441 & 0.25 & 0.31 & 0.31 & 0.15 & 0.36 & 0.31 & 0.36 & 0.38 & 0.29 & 0.30 & 0.30 \\
SCHL43 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 43 & 1 & 0 & 433 & 0.24 & 0.29 & 0.28 & 0.15 & 0.33 & 0.29 & 0.35 & 0.37 & 0.28 & 0.30 & 0.29 \\
SCHL44 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 44 & 1 & 0 & 428 & 0.23 & 0.28 & 0.27 & 0.17 & 0.31 & 0.28 & 0.34 & 0.36 & 0.26 & 0.30 & 0.28 \\
SCHL45 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 45 & 1 & 0 & 429 & 0.22 & 0.27 & 0.26 & 0.17 & 0.28 & 0.27 & 0.33 & 0.32 & 0.24 & 0.28 & 0.27 \\
SCHL46 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 46 & 1 & 0 & 423 & 0.21 & 0.26 & 0.25 & 0.17 & 0.28 & 0.25 & 0.32 & 0.32 & 0.22 & 0.27 & 0.26 \\
SCHL47 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 47 & 1 & 0 & 417 & 0.20 & 0.24 & 0.25 & 0.17 & 0.32 & 0.24 & 0.30 & 0.29 & 0.21 & 0.25 & 0.25 \\
SCHL48 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 48 & 1 & 0 & 409 & 0.19 & 0.23 & 0.22 & 0.17 & 0.24 & 0.22 & 0.29 & 0.27 & 0.19 & 0.25 & 0.23 \\
SCHL49 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 49 & 1 & 0 & 405 & 0.17 & 0.21 & 0.20 & 0.15 & 0.20 & 0.21 & 0.28 & 0.26 & 0.17 & 0.24 & 0.20 \\
SCHL50 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 50 & 1 & 0 & 398 & 0.16 & 0.19 & 0.20 & 0.15 & 0.20 & 0.20 & 0.26 & 0.22 & 0.16 & 0.23 & 0.18 \\
SCHL51 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 51 & 1 & 0 & 396 & 0.15 & 0.18 & 0.18 & 0.15 & 0.20 & 0.17 & 0.23 & 0.21 & 0.14 & 0.22 & 0.17 \\
SCHL52 & SCHOOL PROGRAMS YEAR BEFORE RA - WEEK 52 & 1 & 0 & 390 & 0.13 & 0.16 & 0.18 & 0.15 & 0.17 & 0.16 & 0.22 & 0.18 & 0.13 & 0.21 & 0.16 \\
TRNG1 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 1 & 1 & 0 & 269 & 0.02 & 0.01 & 0.01 & 0.05 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.03 & 0.01 \\
TRNG2 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 2 & 1 & 0 & 270 & 0.01 & 0.01 & 0.01 & 0.05 & 0.00 & 0.01 & 0.01 & 0.01 & 0.02 & 0.03 & 0.01 \\
TRNG3 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 3 & 1 & 0 & 269 & 0.02 & 0.01 & 0.01 & 0.05 & 0.00 & 0.01 & 0.01 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG4 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 4 & 1 & 0 & 269 & 0.01 & 0.02 & 0.01 & 0.05 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG5 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 5 & 1 & 0 & 270 & 0.02 & 0.02 & 0.02 & 0.05 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.03 & 0.01 \\
TRNG6 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 6 & 1 & 0 & 270 & 0.01 & 0.02 & 0.02 & 0.05 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.03 & 0.01 \\
TRNG7 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 7 & 1 & 0 & 269 & 0.01 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.03 & 0.01 \\
TRNG8 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 8 & 1 & 0 & 269 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG9 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 9 & 1 & 0 & 270 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG10 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 10 & 1 & 0 & 268 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.02 & 0.01 & 0.01 & 0.03 & 0.02 \\
TRNG11 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 11 & 1 & 0 & 267 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 & 0.03 & 0.01 \\
TRNG12 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 12 & 1 & 0 & 266 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.04 & 0.01 \\
TRNG13 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 13 & 1 & 0 & 266 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.04 & 0.01 \\
TRNG14 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 14 & 1 & 0 & 267 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.04 & 0.01 \\
TRNG15 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 15 & 1 & 0 & 268 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.04 & 0.02 \\
TRNG16 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 16 & 1 & 0 & 270 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG17 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 17 & 1 & 0 & 269 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.04 & 0.02 \\
TRNG18 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 18 & 1 & 0 & 269 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.04 & 0.02 \\
TRNG19 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 19 & 1 & 0 & 271 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.04 & 0.02 \\
TRNG20 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 20 & 1 & 0 & 270 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.04 & 0.02 \\
TRNG21 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 21 & 1 & 0 & 270 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG22 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 22 & 1 & 0 & 270 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG23 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 23 & 1 & 0 & 270 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG24 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 24 & 1 & 0 & 270 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG25 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 25 & 1 & 0 & 270 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.02 & 0.03 & 0.01 \\
TRNG26 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 26 & 1 & 0 & 269 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.02 & 0.03 & 0.01 \\
TRNG27 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 27 & 1 & 0 & 268 & 0.01 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.02 & 0.03 & 0.02 \\
TRNG28 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 28 & 1 & 0 & 268 & 0.01 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.01 & 0.04 & 0.02 \\
TRNG29 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 29 & 1 & 0 & 267 & 0.01 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.02 & 0.04 & 0.02 \\
TRNG30 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 30 & 1 & 0 & 267 & 0.01 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.01 & 0.04 & 0.02 \\
TRNG31 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 31 & 1 & 0 & 267 & 0.01 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.01 & 0.01 & 0.02 \\
TRNG32 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 32 & 1 & 0 & 266 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.02 \\
TRNG33 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 33 & 1 & 0 & 265 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.02 \\
TRNG34 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 34 & 1 & 0 & 265 & 0.02 & 0.02 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.02 \\
TRNG35 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 35 & 1 & 0 & 265 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.02 \\
TRNG36 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 36 & 1 & 0 & 264 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 \\
TRNG37 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 37 & 1 & 0 & 264 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 \\
TRNG38 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 38 & 1 & 0 & 264 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 \\
TRNG39 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 39 & 1 & 0 & 266 & 0.02 & 0.01 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 \\
TRNG40 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 40 & 1 & 0 & 265 & 0.02 & 0.01 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 \\
TRNG41 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 41 & 1 & 0 & 265 & 0.02 & 0.01 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 \\
TRNG42 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 42 & 1 & 0 & 264 & 0.02 & 0.01 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 \\
TRNG43 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 43 & 1 & 0 & 263 & 0.02 & 0.01 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 \\
TRNG44 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 44 & 1 & 0 & 262 & 0.01 & 0.01 & 0.02 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 \\
TRNG45 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 45 & 1 & 0 & 262 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 \\
TRNG46 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 46 & 1 & 0 & 261 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.01 & 0.02 & 0.01 \\
TRNG47 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 47 & 1 & 0 & 260 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 \\
TRNG48 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 48 & 1 & 0 & 260 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 \\
TRNG49 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 49 & 1 & 0 & 258 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.00 & 0.01 & 0.02 & 0.01 \\
TRNG50 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 50 & 1 & 0 & 258 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.02 & 0.01 \\
TRNG51 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 51 & 1 & 0 & 256 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.01 & 0.01 \\
TRNG52 & TRAINING PROGRAMS YEAR BEFORE RA-WEEK 52 & 1 & 0 & 244 & 0.01 & 0.01 & 0.02 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.01 & 0.01 \\
WORK1 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 1 & 1 & 0 & 537 & 0.25 & 0.24 & 0.28 & 0.20 & 0.17 & 0.20 & 0.21 & 0.18 & 0.27 & 0.23 & 0.27 \\
WORK2 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 2 & 1 & 0 & 548 & 0.26 & 0.24 & 0.29 & 0.15 & 0.22 & 0.21 & 0.21 & 0.18 & 0.28 & 0.22 & 0.27 \\
WORK3 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 3 & 1 & 0 & 551 & 0.27 & 0.25 & 0.30 & 0.15 & 0.22 & 0.21 & 0.21 & 0.18 & 0.29 & 0.22 & 0.29 \\
WORK4 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 4 & 1 & 0 & 552 & 0.28 & 0.25 & 0.31 & 0.23 & 0.24 & 0.22 & 0.22 & 0.19 & 0.30 & 0.22 & 0.29 \\
WORK5 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 5 & 1 & 0 & 556 & 0.28 & 0.26 & 0.32 & 0.23 & 0.24 & 0.22 & 0.23 & 0.19 & 0.30 & 0.21 & 0.30 \\
WORK6 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 6 & 1 & 0 & 554 & 0.29 & 0.26 & 0.32 & 0.21 & 0.24 & 0.22 & 0.23 & 0.21 & 0.30 & 0.22 & 0.31 \\
WORK7 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 7 & 1 & 0 & 554 & 0.30 & 0.26 & 0.32 & 0.21 & 0.24 & 0.23 & 0.23 & 0.19 & 0.31 & 0.22 & 0.33 \\
WORK8 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 8 & 1 & 0 & 555 & 0.30 & 0.27 & 0.32 & 0.21 & 0.24 & 0.24 & 0.23 & 0.20 & 0.31 & 0.22 & 0.33 \\
WORK9 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 9 & 1 & 0 & 557 & 0.31 & 0.27 & 0.32 & 0.21 & 0.27 & 0.24 & 0.23 & 0.21 & 0.31 & 0.21 & 0.32 \\
WORK10 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 10 & 1 & 0 & 557 & 0.31 & 0.28 & 0.31 & 0.21 & 0.22 & 0.25 & 0.23 & 0.22 & 0.31 & 0.21 & 0.32 \\
WORK11 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 11 & 1 & 0 & 552 & 0.31 & 0.28 & 0.32 & 0.21 & 0.20 & 0.25 & 0.23 & 0.22 & 0.32 & 0.24 & 0.33 \\
WORK12 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 12 & 1 & 0 & 549 & 0.32 & 0.29 & 0.33 & 0.18 & 0.25 & 0.25 & 0.23 & 0.22 & 0.32 & 0.25 & 0.33 \\
WORK13 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 13 & 1 & 0 & 551 & 0.32 & 0.29 & 0.34 & 0.18 & 0.25 & 0.26 & 0.23 & 0.23 & 0.33 & 0.25 & 0.32 \\
WORK14 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 14 & 1 & 0 & 553 & 0.32 & 0.29 & 0.34 & 0.18 & 0.25 & 0.26 & 0.23 & 0.23 & 0.33 & 0.27 & 0.33 \\
WORK15 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 15 & 1 & 0 & 555 & 0.32 & 0.29 & 0.33 & 0.18 & 0.28 & 0.26 & 0.23 & 0.23 & 0.34 & 0.28 & 0.32 \\
WORK16 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 16 & 1 & 0 & 561 & 0.32 & 0.30 & 0.34 & 0.25 & 0.32 & 0.26 & 0.24 & 0.22 & 0.33 & 0.32 & 0.32 \\
WORK17 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 17 & 1 & 0 & 562 & 0.32 & 0.30 & 0.32 & 0.24 & 0.32 & 0.26 & 0.24 & 0.22 & 0.33 & 0.31 & 0.32 \\
WORK18 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 18 & 1 & 0 & 567 & 0.32 & 0.30 & 0.33 & 0.24 & 0.35 & 0.27 & 0.25 & 0.21 & 0.34 & 0.31 & 0.32 \\
WORK19 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 19 & 1 & 0 & 565 & 0.32 & 0.31 & 0.34 & 0.27 & 0.32 & 0.28 & 0.25 & 0.20 & 0.34 & 0.31 & 0.33 \\
WORK20 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 20 & 1 & 0 & 556 & 0.32 & 0.30 & 0.35 & 0.24 & 0.38 & 0.28 & 0.25 & 0.20 & 0.33 & 0.31 & 0.33 \\
WORK21 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 21 & 1 & 0 & 557 & 0.33 & 0.31 & 0.35 & 0.27 & 0.42 & 0.28 & 0.26 & 0.19 & 0.33 & 0.30 & 0.32 \\
WORK22 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 22 & 1 & 0 & 558 & 0.33 & 0.31 & 0.36 & 0.24 & 0.42 & 0.28 & 0.26 & 0.20 & 0.33 & 0.29 & 0.32 \\
WORK23 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 23 & 1 & 0 & 552 & 0.33 & 0.31 & 0.35 & 0.24 & 0.42 & 0.27 & 0.26 & 0.20 & 0.34 & 0.30 & 0.32 \\
WORK24 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 24 & 1 & 0 & 546 & 0.34 & 0.32 & 0.35 & 0.22 & 0.42 & 0.27 & 0.28 & 0.22 & 0.34 & 0.29 & 0.31 \\
WORK25 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 25 & 1 & 0 & 543 & 0.34 & 0.32 & 0.35 & 0.20 & 0.42 & 0.27 & 0.28 & 0.24 & 0.35 & 0.31 & 0.31 \\
WORK26 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 26 & 1 & 0 & 542 & 0.33 & 0.32 & 0.35 & 0.19 & 0.42 & 0.28 & 0.29 & 0.23 & 0.36 & 0.31 & 0.31 \\
WORK27 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 27 & 1 & 0 & 543 & 0.33 & 0.33 & 0.35 & 0.23 & 0.42 & 0.29 & 0.28 & 0.25 & 0.36 & 0.31 & 0.33 \\
WORK28 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 28 & 1 & 0 & 541 & 0.33 & 0.33 & 0.36 & 0.26 & 0.38 & 0.29 & 0.28 & 0.25 & 0.36 & 0.29 & 0.35 \\
WORK29 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 29 & 1 & 0 & 535 & 0.33 & 0.33 & 0.36 & 0.26 & 0.42 & 0.28 & 0.25 & 0.25 & 0.37 & 0.31 & 0.34 \\
WORK30 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 30 & 1 & 0 & 531 & 0.33 & 0.33 & 0.36 & 0.28 & 0.45 & 0.29 & 0.24 & 0.26 & 0.36 & 0.29 & 0.34 \\
WORK31 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 31 & 1 & 0 & 531 & 0.33 & 0.34 & 0.36 & 0.26 & 0.45 & 0.29 & 0.24 & 0.28 & 0.36 & 0.28 & 0.35 \\
WORK32 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 32 & 1 & 0 & 530 & 0.33 & 0.33 & 0.36 & 0.30 & 0.48 & 0.29 & 0.25 & 0.28 & 0.35 & 0.28 & 0.35 \\
WORK33 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 33 & 1 & 0 & 515 & 0.33 & 0.33 & 0.37 & 0.30 & 0.45 & 0.30 & 0.25 & 0.27 & 0.36 & 0.26 & 0.34 \\
WORK34 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 34 & 1 & 0 & 513 & 0.33 & 0.33 & 0.37 & 0.30 & 0.38 & 0.30 & 0.25 & 0.27 & 0.36 & 0.26 & 0.34 \\
WORK35 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 35 & 1 & 0 & 507 & 0.33 & 0.33 & 0.38 & 0.28 & 0.40 & 0.30 & 0.25 & 0.26 & 0.36 & 0.25 & 0.34 \\
WORK36 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 36 & 1 & 0 & 502 & 0.33 & 0.33 & 0.39 & 0.28 & 0.38 & 0.30 & 0.25 & 0.26 & 0.36 & 0.24 & 0.34 \\
WORK37 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 37 & 1 & 0 & 494 & 0.33 & 0.32 & 0.37 & 0.33 & 0.35 & 0.28 & 0.26 & 0.25 & 0.37 & 0.25 & 0.34 \\
WORK38 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 38 & 1 & 0 & 491 & 0.33 & 0.32 & 0.37 & 0.33 & 0.35 & 0.29 & 0.27 & 0.26 & 0.36 & 0.25 & 0.33 \\
WORK39 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 39 & 1 & 0 & 480 & 0.32 & 0.32 & 0.38 & 0.28 & 0.41 & 0.29 & 0.27 & 0.26 & 0.35 & 0.26 & 0.34 \\
WORK40 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 40 & 1 & 0 & 468 & 0.31 & 0.32 & 0.37 & 0.30 & 0.41 & 0.28 & 0.28 & 0.29 & 0.35 & 0.24 & 0.35 \\
WORK41 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 41 & 1 & 0 & 466 & 0.30 & 0.31 & 0.38 & 0.28 & 0.41 & 0.28 & 0.25 & 0.28 & 0.34 & 0.21 & 0.35 \\
WORK42 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 42 & 1 & 0 & 459 & 0.30 & 0.31 & 0.38 & 0.23 & 0.41 & 0.28 & 0.26 & 0.26 & 0.35 & 0.21 & 0.35 \\
WORK43 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 43 & 1 & 0 & 456 & 0.30 & 0.31 & 0.38 & 0.19 & 0.32 & 0.28 & 0.25 & 0.25 & 0.35 & 0.20 & 0.34 \\
WORK44 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 44 & 1 & 0 & 452 & 0.29 & 0.31 & 0.38 & 0.14 & 0.29 & 0.28 & 0.25 & 0.25 & 0.34 & 0.19 & 0.33 \\
WORK45 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 45 & 1 & 0 & 447 & 0.28 & 0.30 & 0.38 & 0.14 & 0.29 & 0.27 & 0.24 & 0.24 & 0.32 & 0.20 & 0.32 \\
WORK46 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 46 & 1 & 0 & 440 & 0.28 & 0.29 & 0.36 & 0.19 & 0.27 & 0.27 & 0.23 & 0.25 & 0.30 & 0.19 & 0.32 \\
WORK47 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 47 & 1 & 0 & 437 & 0.27 & 0.28 & 0.34 & 0.19 & 0.24 & 0.25 & 0.23 & 0.26 & 0.29 & 0.20 & 0.32 \\
WORK48 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 48 & 1 & 0 & 429 & 0.26 & 0.27 & 0.31 & 0.23 & 0.27 & 0.24 & 0.22 & 0.24 & 0.29 & 0.19 & 0.29 \\
WORK49 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 49 & 1 & 0 & 425 & 0.26 & 0.26 & 0.30 & 0.23 & 0.24 & 0.23 & 0.21 & 0.23 & 0.27 & 0.20 & 0.27 \\
WORK50 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 50 & 1 & 0 & 419 & 0.24 & 0.24 & 0.30 & 0.14 & 0.24 & 0.22 & 0.20 & 0.21 & 0.26 & 0.19 & 0.26 \\
WORK51 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 51 & 1 & 0 & 413 & 0.23 & 0.22 & 0.28 & 0.16 & 0.17 & 0.21 & 0.20 & 0.21 & 0.24 & 0.17 & 0.25 \\
WORK52 & WORK EXPERIENCE YEAR BEFORE RA - WEEK 52 & 1 & 0 & 401 & 0.22 & 0.21 & 0.26 & 0.16 & 0.17 & 0.20 & 0.19 & 0.19 & 0.22 & 0.18 & 0.22 \\
WELF1 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 1 & 1 & 0 & 1429 & 0.57 & 0.55 & 0.55 & 0.78 & 0.51 & 0.58 & 0.58 & 0.44 & 0.52 & 0.51 & 0.50 \\
WELF2 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 2 & 1 & 0 & 1427 & 0.57 & 0.55 & 0.55 & 0.80 & 0.51 & 0.58 & 0.58 & 0.44 & 0.52 & 0.51 & 0.50 \\
WELF3 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 3 & 1 & 0 & 1425 & 0.57 & 0.55 & 0.54 & 0.80 & 0.49 & 0.58 & 0.58 & 0.44 & 0.52 & 0.51 & 0.50 \\
WELF4 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 4 & 1 & 0 & 1417 & 0.57 & 0.55 & 0.54 & 0.80 & 0.49 & 0.58 & 0.59 & 0.45 & 0.51 & 0.51 & 0.50 \\
WELF5 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 5 & 1 & 0 & 1411 & 0.58 & 0.55 & 0.54 & 0.80 & 0.49 & 0.59 & 0.59 & 0.44 & 0.52 & 0.52 & 0.49 \\
WELF6 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 6 & 1 & 0 & 1407 & 0.58 & 0.55 & 0.55 & 0.80 & 0.49 & 0.59 & 0.59 & 0.45 & 0.52 & 0.51 & 0.50 \\
WELF7 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 7 & 1 & 0 & 1405 & 0.58 & 0.55 & 0.56 & 0.80 & 0.46 & 0.59 & 0.58 & 0.44 & 0.52 & 0.53 & 0.50 \\
WELF8 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 8 & 1 & 0 & 1395 & 0.58 & 0.55 & 0.56 & 0.80 & 0.46 & 0.59 & 0.58 & 0.43 & 0.52 & 0.53 & 0.50 \\
WELF9 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 9 & 1 & 0 & 1395 & 0.58 & 0.56 & 0.55 & 0.78 & 0.46 & 0.59 & 0.58 & 0.43 & 0.53 & 0.53 & 0.50 \\
WELF10 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 10 & 1 & 0 & 1393 & 0.58 & 0.55 & 0.56 & 0.78 & 0.47 & 0.59 & 0.58 & 0.44 & 0.53 & 0.53 & 0.50 \\
WELF11 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 11 & 1 & 0 & 1390 & 0.59 & 0.56 & 0.56 & 0.78 & 0.47 & 0.59 & 0.59 & 0.44 & 0.53 & 0.55 & 0.50 \\
WELF12 & WELFARE RECEIPT YEAR BEFORE RA - MONTH 12 & 1 & 0 & 1380 & 0.59 & 0.56 & 0.55 & 0.78 & 0.47 & 0.59 & 0.59 & 0.45 & 0.53 & 0.54 & 0.51 \\
currjob & had job at random assignment & 1 & 0 & 401 & 0.22 & 0.21 & 0.26 & 0.16 & 0.17 & 0.20 & 0.19 & 0.19 & 0.22 & 0.18 & 0.22 \\
female & 1 if female; 0 if male & 1 & 0 & 0 & 0.47 & 0.38 & 0.49 & 0.65 & 0.36 & 0.46 & 0.43 & 0.39 & 0.42 & 0.46 & 0.44 \\
JCAXH1 & TOOK ACADEMICS IN JOB CORPS IN WEEK 1 & 1 & 1 & 405 & 0.03 & 0.00 & 0.00 & 0.00 & 0.00 & 0.12 & 0.05 & 0.05 & 0.04 & 0.04 & 0.02 \\
JCAXH2 & TOOK ACADEMICS IN JOB CORPS IN WEEK 2 & 1 & 1 & 407 & 0.04 & 0.00 & 0.00 & 0.00 & 0.00 & 0.20 & 0.12 & 0.11 & 0.09 & 0.11 & 0.06 \\
JCAXH3 & TOOK ACADEMICS IN JOB CORPS IN WEEK 3 & 1 & 1 & 410 & 0.07 & 0.00 & 0.00 & 0.00 & 0.00 & 0.33 & 0.24 & 0.20 & 0.16 & 0.16 & 0.14 \\
JCAXH4 & TOOK ACADEMICS IN JOB CORPS IN WEEK 4 & 1 & 1 & 421 & 0.10 & 0.00 & 0.00 & 0.00 & 0.00 & 0.46 & 0.37 & 0.36 & 0.26 & 0.25 & 0.23 \\
JCAXH5 & TOOK ACADEMICS IN JOB CORPS IN WEEK 5 & 1 & 1 & 424 & 0.12 & 0.00 & 0.00 & 0.00 & 0.00 & 0.58 & 0.47 & 0.53 & 0.36 & 0.39 & 0.35 \\
JCAXH6 & TOOK ACADEMICS IN JOB CORPS IN WEEK 6 & 1 & 1 & 427 & 0.14 & 0.00 & 0.00 & 0.00 & 0.00 & 0.67 & 0.56 & 0.64 & 0.44 & 0.52 & 0.44 \\
JCAXH7 & TOOK ACADEMICS IN JOB CORPS IN WEEK 7 & 1 & 1 & 427 & 0.15 & 0.00 & 0.00 & 0.00 & 0.00 & 0.70 & 0.65 & 0.72 & 0.49 & 0.58 & 0.50 \\
JCAXH8 & TOOK ACADEMICS IN JOB CORPS IN WEEK 8 & 1 & 1 & 431 & 0.15 & 0.00 & 0.00 & 0.00 & 0.00 & 0.71 & 0.71 & 0.75 & 0.50 & 0.58 & 0.55 \\
JCAXH9 & TOOK ACADEMICS IN JOB CORPS IN WEEK 9 & 1 & 1 & 428 & 0.15 & 0.00 & 0.00 & 0.00 & 0.00 & 0.71 & 0.74 & 0.76 & 0.49 & 0.60 & 0.58 \\
JCAXH10 & TOOK ACADEMICS IN JOB CORPS IN WEEK 10 & 1 & 1 & 427 & 0.15 & 0.00 & 0.00 & 0.00 & 0.00 & 0.69 & 0.74 & 0.79 & 0.48 & 0.62 & 0.57 \\
JCAXH11 & TOOK ACADEMICS IN JOB CORPS IN WEEK 11 & 1 & 1 & 425 & 0.15 & 0.00 & 0.00 & 0.00 & 0.00 & 0.66 & 0.75 & 0.80 & 0.48 & 0.64 & 0.57 \\
JCAXH12 & TOOK ACADEMICS IN JOB CORPS IN WEEK 12 & 1 & 1 & 428 & 0.14 & 0.00 & 0.00 & 0.00 & 0.00 & 0.64 & 0.76 & 0.80 & 0.45 & 0.62 & 0.54 \\
JCAXH13 & TOOK ACADEMICS IN JOB CORPS IN WEEK 13 & 1 & 1 & 428 & 0.14 & 0.00 & 0.00 & 0.00 & 0.00 & 0.61 & 0.76 & 0.80 & 0.43 & 0.62 & 0.53 \\
JCAXH14 & TOOK ACADEMICS IN JOB CORPS IN WEEK 14 & 1 & 1 & 429 & 0.13 & 0.00 & 0.00 & 0.00 & 0.00 & 0.59 & 0.76 & 0.79 & 0.40 & 0.59 & 0.54 \\
JCAXH15 & TOOK ACADEMICS IN JOB CORPS IN WEEK 15 & 1 & 1 & 425 & 0.13 & 0.00 & 0.00 & 0.00 & 0.00 & 0.56 & 0.75 & 0.79 & 0.38 & 0.57 & 0.53 \\
JCAXH16 & TOOK ACADEMICS IN JOB CORPS IN WEEK 16 & 1 & 1 & 417 & 0.12 & 0.00 & 0.00 & 0.00 & 0.00 & 0.54 & 0.75 & 0.80 & 0.36 & 0.57 & 0.51 \\
JCAXH17 & TOOK ACADEMICS IN JOB CORPS IN WEEK 17 & 1 & 1 & 412 & 0.12 & 0.00 & 0.00 & 0.00 & 0.00 & 0.51 & 0.74 & 0.79 & 0.34 & 0.57 & 0.49 \\
JCAXH18 & TOOK ACADEMICS IN JOB CORPS IN WEEK 18 & 1 & 1 & 412 & 0.12 & 0.00 & 0.00 & 0.00 & 0.00 & 0.49 & 0.74 & 0.80 & 0.32 & 0.55 & 0.48 \\
JCAXH19 & TOOK ACADEMICS IN JOB CORPS IN WEEK 19 & 1 & 1 & 412 & 0.11 & 0.00 & 0.00 & 0.00 & 0.00 & 0.47 & 0.74 & 0.80 & 0.30 & 0.54 & 0.46 \\
JCAXH20 & TOOK ACADEMICS IN JOB CORPS IN WEEK 20 & 1 & 1 & 408 & 0.11 & 0.00 & 0.00 & 0.00 & 0.00 & 0.44 & 0.75 & 0.81 & 0.29 & 0.51 & 0.44 \\
JCAXH21 & TOOK ACADEMICS IN JOB CORPS IN WEEK 21 & 1 & 1 & 404 & 0.10 & 0.00 & 0.00 & 0.00 & 0.00 & 0.41 & 0.74 & 0.80 & 0.27 & 0.51 & 0.43 \\
JCAXH22 & TOOK ACADEMICS IN JOB CORPS IN WEEK 22 & 1 & 1 & 403 & 0.10 & 0.00 & 0.00 & 0.00 & 0.00 & 0.40 & 0.73 & 0.78 & 0.25 & 0.51 & 0.41 \\
JCAXH23 & TOOK ACADEMICS IN JOB CORPS IN WEEK 23 & 1 & 1 & 403 & 0.09 & 0.00 & 0.00 & 0.00 & 0.00 & 0.37 & 0.72 & 0.78 & 0.24 & 0.49 & 0.39 \\
JCAXH24 & TOOK ACADEMICS IN JOB CORPS IN WEEK 24 & 1 & 1 & 402 & 0.09 & 0.00 & 0.00 & 0.00 & 0.00 & 0.36 & 0.71 & 0.78 & 0.23 & 0.49 & 0.38 \\
JCAXH25 & TOOK ACADEMICS IN JOB CORPS IN WEEK 25 & 1 & 1 & 399 & 0.08 & 0.00 & 0.00 & 0.00 & 0.00 & 0.35 & 0.71 & 0.77 & 0.21 & 0.47 & 0.38 \\
JCAXH26 & TOOK ACADEMICS IN JOB CORPS IN WEEK 26 & 1 & 1 & 399 & 0.07 & 0.00 & 0.00 & 0.00 & 0.00 & 0.32 & 0.70 & 0.76 & 0.20 & 0.47 & 0.38 \\
JCAXH27 & TOOK ACADEMICS IN JOB CORPS IN WEEK 27 & 1 & 1 & 397 & 0.07 & 0.00 & 0.00 & 0.00 & 0.00 & 0.30 & 0.70 & 0.76 & 0.19 & 0.47 & 0.36 \\
JCAXH28 & TOOK ACADEMICS IN JOB CORPS IN WEEK 28 & 1 & 1 & 397 & 0.07 & 0.00 & 0.00 & 0.00 & 0.00 & 0.28 & 0.69 & 0.73 & 0.18 & 0.48 & 0.34 \\
JCAXH29 & TOOK ACADEMICS IN JOB CORPS IN WEEK 29 & 1 & 1 & 392 & 0.07 & 0.00 & 0.00 & 0.00 & 0.00 & 0.27 & 0.69 & 0.73 & 0.17 & 0.48 & 0.33 \\
JCAXH30 & TOOK ACADEMICS IN JOB CORPS IN WEEK 30 & 1 & 1 & 388 & 0.06 & 0.00 & 0.00 & 0.00 & 0.00 & 0.24 & 0.69 & 0.72 & 0.15 & 0.49 & 0.32 \\
JCAXH31 & TOOK ACADEMICS IN JOB CORPS IN WEEK 31 & 1 & 1 & 388 & 0.06 & 0.00 & 0.00 & 0.00 & 0.00 & 0.24 & 0.69 & 0.69 & 0.14 & 0.48 & 0.31 \\
JCAXH32 & TOOK ACADEMICS IN JOB CORPS IN WEEK 32 & 1 & 1 & 383 & 0.06 & 0.00 & 0.00 & 0.00 & 0.00 & 0.22 & 0.69 & 0.69 & 0.13 & 0.47 & 0.30 \\
JCAXH33 & TOOK ACADEMICS IN JOB CORPS IN WEEK 33 & 1 & 1 & 380 & 0.06 & 0.00 & 0.00 & 0.00 & 0.00 & 0.21 & 0.69 & 0.67 & 0.11 & 0.45 & 0.30 \\
JCAXH34 & TOOK ACADEMICS IN JOB CORPS IN WEEK 34 & 1 & 1 & 376 & 0.05 & 0.00 & 0.00 & 0.00 & 0.00 & 0.19 & 0.69 & 0.67 & 0.10 & 0.46 & 0.28 \\
JCAXH35 & TOOK ACADEMICS IN JOB CORPS IN WEEK 35 & 1 & 1 & 370 & 0.05 & 0.00 & 0.00 & 0.00 & 0.00 & 0.19 & 0.69 & 0.67 & 0.09 & 0.46 & 0.27 \\
JCAXH36 & TOOK ACADEMICS IN JOB CORPS IN WEEK 36 & 1 & 1 & 368 & 0.05 & 0.00 & 0.00 & 0.00 & 0.00 & 0.18 & 0.68 & 0.66 & 0.09 & 0.45 & 0.26 \\
JCAXH37 & TOOK ACADEMICS IN JOB CORPS IN WEEK 37 & 1 & 1 & 366 & 0.05 & 0.00 & 0.00 & 0.00 & 0.00 & 0.16 & 0.68 & 0.66 & 0.08 & 0.45 & 0.26 \\
JCAXH38 & TOOK ACADEMICS IN JOB CORPS IN WEEK 38 & 1 & 1 & 363 & 0.04 & 0.00 & 0.00 & 0.00 & 0.00 & 0.15 & 0.68 & 0.66 & 0.08 & 0.45 & 0.25 \\
JCAXH39 & TOOK ACADEMICS IN JOB CORPS IN WEEK 39 & 1 & 1 & 361 & 0.04 & 0.00 & 0.00 & 0.00 & 0.00 & 0.14 & 0.68 & 0.66 & 0.07 & 0.43 & 0.24 \\
JCAXH40 & TOOK ACADEMICS IN JOB CORPS IN WEEK 40 & 1 & 1 & 358 & 0.04 & 0.00 & 0.00 & 0.00 & 0.00 & 0.13 & 0.68 & 0.65 & 0.06 & 0.42 & 0.23 \\
JCAXH41 & TOOK ACADEMICS IN JOB CORPS IN WEEK 41 & 1 & 1 & 358 & 0.04 & 0.00 & 0.00 & 0.00 & 0.00 & 0.12 & 0.67 & 0.64 & 0.06 & 0.41 & 0.23 \\
JCAXH42 & TOOK ACADEMICS IN JOB CORPS IN WEEK 42 & 1 & 1 & 354 & 0.04 & 0.00 & 0.00 & 0.00 & 0.00 & 0.11 & 0.67 & 0.64 & 0.05 & 0.43 & 0.23 \\
JCAXH43 & TOOK ACADEMICS IN JOB CORPS IN WEEK 43 & 1 & 1 & 349 & 0.03 & 0.00 & 0.00 & 0.00 & 0.00 & 0.09 & 0.67 & 0.64 & 0.04 & 0.43 & 0.22 \\
JCAXH44 & TOOK ACADEMICS IN JOB CORPS IN WEEK 44 & 1 & 1 & 347 & 0.03 & 0.00 & 0.00 & 0.00 & 0.00 & 0.08 & 0.66 & 0.64 & 0.04 & 0.42 & 0.21 \\
JCAXH45 & TOOK ACADEMICS IN JOB CORPS IN WEEK 45 & 1 & 1 & 345 & 0.03 & 0.00 & 0.00 & 0.00 & 0.00 & 0.07 & 0.67 & 0.64 & 0.03 & 0.42 & 0.20 \\
JCAXH46 & TOOK ACADEMICS IN JOB CORPS IN WEEK 46 & 1 & 1 & 344 & 0.03 & 0.00 & 0.00 & 0.00 & 0.00 & 0.06 & 0.66 & 0.63 & 0.03 & 0.42 & 0.18 \\
JCAXH47 & TOOK ACADEMICS IN JOB CORPS IN WEEK 47 & 1 & 1 & 342 & 0.03 & 0.00 & 0.00 & 0.00 & 0.00 & 0.05 & 0.66 & 0.62 & 0.02 & 0.42 & 0.18 \\
JCAXH48 & TOOK ACADEMICS IN JOB CORPS IN WEEK 48 & 1 & 1 & 340 & 0.03 & 0.00 & 0.00 & 0.00 & 0.00 & 0.04 & 0.66 & 0.62 & 0.01 & 0.41 & 0.17 \\
JCAXH49 & TOOK ACADEMICS IN JOB CORPS IN WEEK 49 & 1 & 1 & 335 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.03 & 0.67 & 0.62 & 0.01 & 0.41 & 0.15 \\
JCAXH50 & TOOK ACADEMICS IN JOB CORPS IN WEEK 50 & 1 & 1 & 332 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.02 & 0.67 & 0.60 & 0.01 & 0.41 & 0.15 \\
JCAXH51 & TOOK ACADEMICS IN JOB CORPS IN WEEK 51 & 1 & 1 & 330 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.02 & 0.67 & 0.59 & 0.01 & 0.41 & 0.14 \\
JCAXH52 & TOOK ACADEMICS IN JOB CORPS IN WEEK 52 & 1 & 1 & 329 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.01 & 0.67 & 0.58 & 0.00 & 0.41 & 0.14 \\
EDTNX1 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 1 & 1 & 1 & 469 & 0.15 & 0.18 & 0.18 & 0.17 & 0.19 & 0.16 & 0.21 & 0.19 & 0.13 & 0.23 & 0.14 \\
EDTNX2 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 2 & 1 & 1 & 517 & 0.14 & 0.17 & 0.16 & 0.14 & 0.19 & 0.12 & 0.18 & 0.16 & 0.10 & 0.17 & 0.10 \\
EDTNX3 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 3 & 1 & 1 & 533 & 0.14 & 0.17 & 0.14 & 0.14 & 0.24 & 0.10 & 0.14 & 0.13 & 0.09 & 0.17 & 0.08 \\
EDTNX4 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 4 & 1 & 1 & 540 & 0.13 & 0.18 & 0.13 & 0.16 & 0.24 & 0.08 & 0.10 & 0.12 & 0.07 & 0.16 & 0.05 \\
EDTNX5 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 5 & 1 & 1 & 536 & 0.13 & 0.19 & 0.14 & 0.16 & 0.21 & 0.07 & 0.08 & 0.11 & 0.06 & 0.11 & 0.04 \\
EDTNX6 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 6 & 1 & 1 & 537 & 0.14 & 0.20 & 0.14 & 0.16 & 0.19 & 0.07 & 0.06 & 0.09 & 0.05 & 0.09 & 0.02 \\
EDTNX7 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 7 & 1 & 1 & 534 & 0.14 & 0.20 & 0.14 & 0.19 & 0.17 & 0.06 & 0.06 & 0.07 & 0.05 & 0.08 & 0.02 \\
EDTNX8 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 8 & 1 & 1 & 538 & 0.15 & 0.20 & 0.15 & 0.21 & 0.19 & 0.07 & 0.06 & 0.06 & 0.04 & 0.08 & 0.02 \\
EDTNX9 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 9 & 1 & 1 & 531 & 0.15 & 0.21 & 0.15 & 0.21 & 0.19 & 0.07 & 0.05 & 0.05 & 0.04 & 0.08 & 0.02 \\
EDTNX10 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 10 & 1 & 1 & 534 & 0.15 & 0.21 & 0.15 & 0.23 & 0.21 & 0.07 & 0.06 & 0.05 & 0.04 & 0.08 & 0.02 \\
EDTNX11 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 11 & 1 & 1 & 532 & 0.15 & 0.22 & 0.16 & 0.23 & 0.21 & 0.07 & 0.05 & 0.04 & 0.03 & 0.08 & 0.02 \\
EDTNX12 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 12 & 1 & 1 & 529 & 0.15 & 0.22 & 0.17 & 0.21 & 0.21 & 0.08 & 0.05 & 0.05 & 0.03 & 0.08 & 0.02 \\
EDTNX13 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 13 & 1 & 1 & 531 & 0.15 & 0.22 & 0.17 & 0.21 & 0.21 & 0.08 & 0.05 & 0.05 & 0.03 & 0.07 & 0.02 \\
EDTNX14 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 14 & 1 & 1 & 533 & 0.15 & 0.23 & 0.18 & 0.21 & 0.24 & 0.08 & 0.04 & 0.05 & 0.03 & 0.07 & 0.02 \\
EDTNX15 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 15 & 1 & 1 & 530 & 0.15 & 0.23 & 0.18 & 0.21 & 0.24 & 0.09 & 0.04 & 0.06 & 0.04 & 0.07 & 0.02 \\
EDTNX16 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 16 & 1 & 1 & 523 & 0.15 & 0.23 & 0.18 & 0.19 & 0.24 & 0.09 & 0.05 & 0.06 & 0.04 & 0.07 & 0.02 \\
EDTNX17 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 17 & 1 & 1 & 521 & 0.15 & 0.24 & 0.18 & 0.21 & 0.24 & 0.09 & 0.04 & 0.06 & 0.04 & 0.08 & 0.02 \\
EDTNX18 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 18 & 1 & 1 & 518 & 0.15 & 0.24 & 0.19 & 0.23 & 0.29 & 0.09 & 0.05 & 0.06 & 0.04 & 0.07 & 0.02 \\
EDTNX19 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 19 & 1 & 1 & 513 & 0.15 & 0.24 & 0.20 & 0.23 & 0.26 & 0.10 & 0.05 & 0.06 & 0.04 & 0.07 & 0.02 \\
EDTNX20 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 20 & 1 & 1 & 510 & 0.15 & 0.24 & 0.20 & 0.26 & 0.26 & 0.10 & 0.05 & 0.06 & 0.05 & 0.07 & 0.01 \\
EDTNX21 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 21 & 1 & 1 & 507 & 0.15 & 0.25 & 0.20 & 0.26 & 0.26 & 0.10 & 0.05 & 0.07 & 0.05 & 0.07 & 0.02 \\
EDTNX22 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 22 & 1 & 1 & 507 & 0.15 & 0.25 & 0.20 & 0.26 & 0.31 & 0.11 & 0.06 & 0.07 & 0.05 & 0.07 & 0.01 \\
EDTNX23 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 23 & 1 & 1 & 504 & 0.16 & 0.25 & 0.19 & 0.26 & 0.31 & 0.11 & 0.06 & 0.07 & 0.05 & 0.09 & 0.01 \\
EDTNX24 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 24 & 1 & 1 & 503 & 0.16 & 0.25 & 0.19 & 0.23 & 0.31 & 0.11 & 0.05 & 0.07 & 0.04 & 0.09 & 0.01 \\
EDTNX25 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 25 & 1 & 1 & 499 & 0.16 & 0.26 & 0.19 & 0.21 & 0.31 & 0.11 & 0.05 & 0.07 & 0.05 & 0.08 & 0.01 \\
EDTNX26 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 26 & 1 & 1 & 494 & 0.16 & 0.26 & 0.20 & 0.21 & 0.29 & 0.12 & 0.05 & 0.08 & 0.05 & 0.08 & 0.01 \\
EDTNX27 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 27 & 1 & 1 & 489 & 0.16 & 0.26 & 0.21 & 0.21 & 0.31 & 0.12 & 0.06 & 0.08 & 0.05 & 0.08 & 0.01 \\
EDTNX28 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 28 & 1 & 1 & 490 & 0.16 & 0.26 & 0.21 & 0.26 & 0.31 & 0.13 & 0.06 & 0.08 & 0.05 & 0.08 & 0.02 \\
EDTNX29 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 29 & 1 & 1 & 487 & 0.17 & 0.25 & 0.22 & 0.26 & 0.33 & 0.13 & 0.07 & 0.08 & 0.05 & 0.08 & 0.02 \\
EDTNX30 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 30 & 1 & 1 & 483 & 0.17 & 0.26 & 0.22 & 0.26 & 0.33 & 0.13 & 0.06 & 0.08 & 0.05 & 0.08 & 0.02 \\
EDTNX31 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 31 & 1 & 1 & 479 & 0.17 & 0.25 & 0.21 & 0.28 & 0.33 & 0.13 & 0.06 & 0.07 & 0.06 & 0.08 & 0.02 \\
EDTNX32 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 32 & 1 & 1 & 471 & 0.17 & 0.25 & 0.21 & 0.28 & 0.31 & 0.13 & 0.07 & 0.08 & 0.06 & 0.08 & 0.02 \\
EDTNX33 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 33 & 1 & 1 & 471 & 0.17 & 0.25 & 0.21 & 0.26 & 0.31 & 0.13 & 0.07 & 0.08 & 0.06 & 0.09 & 0.02 \\
EDTNX34 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 34 & 1 & 1 & 472 & 0.17 & 0.25 & 0.22 & 0.26 & 0.31 & 0.13 & 0.07 & 0.09 & 0.06 & 0.10 & 0.02 \\
EDTNX35 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 35 & 1 & 1 & 470 & 0.17 & 0.25 & 0.22 & 0.26 & 0.31 & 0.13 & 0.07 & 0.09 & 0.07 & 0.08 & 0.02 \\
EDTNX36 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 36 & 1 & 1 & 467 & 0.17 & 0.25 & 0.22 & 0.26 & 0.33 & 0.14 & 0.07 & 0.08 & 0.07 & 0.08 & 0.02 \\
EDTNX37 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 37 & 1 & 1 & 464 & 0.18 & 0.25 & 0.22 & 0.26 & 0.33 & 0.14 & 0.07 & 0.08 & 0.07 & 0.08 & 0.02 \\
EDTNX38 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 38 & 1 & 1 & 464 & 0.18 & 0.25 & 0.20 & 0.26 & 0.33 & 0.14 & 0.07 & 0.07 & 0.08 & 0.08 & 0.03 \\
EDTNX39 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 39 & 1 & 1 & 464 & 0.18 & 0.25 & 0.20 & 0.26 & 0.33 & 0.14 & 0.07 & 0.07 & 0.08 & 0.08 & 0.02 \\
EDTNX40 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 40 & 1 & 1 & 463 & 0.18 & 0.25 & 0.20 & 0.23 & 0.31 & 0.14 & 0.07 & 0.07 & 0.08 & 0.08 & 0.02 \\
EDTNX41 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 41 & 1 & 1 & 461 & 0.18 & 0.25 & 0.19 & 0.23 & 0.31 & 0.14 & 0.07 & 0.07 & 0.08 & 0.07 & 0.03 \\
EDTNX42 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 42 & 1 & 1 & 457 & 0.18 & 0.24 & 0.20 & 0.23 & 0.29 & 0.14 & 0.07 & 0.07 & 0.09 & 0.09 & 0.03 \\
EDTNX43 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 43 & 1 & 1 & 453 & 0.18 & 0.24 & 0.20 & 0.23 & 0.31 & 0.14 & 0.07 & 0.07 & 0.09 & 0.09 & 0.03 \\
EDTNX44 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 44 & 1 & 1 & 449 & 0.18 & 0.24 & 0.20 & 0.23 & 0.27 & 0.14 & 0.07 & 0.07 & 0.09 & 0.09 & 0.03 \\
EDTNX45 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 45 & 1 & 1 & 446 & 0.18 & 0.24 & 0.21 & 0.23 & 0.24 & 0.14 & 0.07 & 0.07 & 0.09 & 0.09 & 0.03 \\
EDTNX46 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 46 & 1 & 1 & 446 & 0.19 & 0.24 & 0.21 & 0.21 & 0.24 & 0.14 & 0.07 & 0.07 & 0.09 & 0.10 & 0.03 \\
EDTNX47 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 47 & 1 & 1 & 439 & 0.19 & 0.24 & 0.22 & 0.21 & 0.22 & 0.15 & 0.07 & 0.07 & 0.10 & 0.10 & 0.03 \\
EDTNX48 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 48 & 1 & 1 & 433 & 0.19 & 0.24 & 0.22 & 0.21 & 0.22 & 0.15 & 0.07 & 0.07 & 0.10 & 0.10 & 0.03 \\
EDTNX49 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 49 & 1 & 1 & 431 & 0.18 & 0.23 & 0.23 & 0.21 & 0.22 & 0.16 & 0.07 & 0.07 & 0.10 & 0.10 & 0.03 \\
EDTNX50 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 50 & 1 & 1 & 423 & 0.19 & 0.23 & 0.23 & 0.23 & 0.22 & 0.16 & 0.07 & 0.07 & 0.10 & 0.09 & 0.03 \\
EDTNX51 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 51 & 1 & 1 & 419 & 0.19 & 0.23 & 0.23 & 0.23 & 0.22 & 0.16 & 0.07 & 0.07 & 0.11 & 0.08 & 0.03 \\
EDTNX52 & IN AN EDUC/TRNING/JC PRGRM IN WEEK 52 & 1 & 1 & 418 & 0.19 & 0.23 & 0.24 & 0.23 & 0.22 & 0.16 & 0.07 & 0.07 & 0.11 & 0.07 & 0.03 \\
EDAXH1 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 1 & 1 & 1 & 567 & 0.14 & 0.17 & 0.17 & 0.15 & 0.17 & 0.15 & 0.20 & 0.18 & 0.12 & 0.20 & 0.14 \\
EDAXH2 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 2 & 1 & 1 & 623 & 0.12 & 0.16 & 0.14 & 0.12 & 0.12 & 0.11 & 0.16 & 0.15 & 0.08 & 0.14 & 0.09 \\
EDAXH3 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 3 & 1 & 1 & 642 & 0.11 & 0.16 & 0.12 & 0.12 & 0.12 & 0.08 & 0.13 & 0.12 & 0.07 & 0.13 & 0.07 \\
EDAXH4 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 4 & 1 & 1 & 650 & 0.11 & 0.16 & 0.11 & 0.14 & 0.12 & 0.07 & 0.09 & 0.11 & 0.06 & 0.12 & 0.04 \\
EDAXH5 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 5 & 1 & 1 & 651 & 0.11 & 0.17 & 0.12 & 0.14 & 0.10 & 0.06 & 0.07 & 0.09 & 0.05 & 0.09 & 0.03 \\
EDAXH6 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 6 & 1 & 1 & 655 & 0.11 & 0.18 & 0.12 & 0.14 & 0.10 & 0.06 & 0.06 & 0.06 & 0.04 & 0.07 & 0.02 \\
EDAXH7 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 7 & 1 & 1 & 655 & 0.12 & 0.18 & 0.12 & 0.16 & 0.12 & 0.06 & 0.05 & 0.06 & 0.04 & 0.07 & 0.01 \\
EDAXH8 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 8 & 1 & 1 & 656 & 0.12 & 0.19 & 0.14 & 0.19 & 0.15 & 0.06 & 0.05 & 0.04 & 0.03 & 0.07 & 0.01 \\
EDAXH9 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 9 & 1 & 1 & 652 & 0.12 & 0.19 & 0.13 & 0.19 & 0.15 & 0.06 & 0.05 & 0.03 & 0.03 & 0.07 & 0.01 \\
EDAXH10 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 10 & 1 & 1 & 655 & 0.12 & 0.19 & 0.13 & 0.21 & 0.15 & 0.06 & 0.05 & 0.03 & 0.03 & 0.07 & 0.01 \\
EDAXH11 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 11 & 1 & 1 & 656 & 0.12 & 0.19 & 0.14 & 0.21 & 0.15 & 0.06 & 0.05 & 0.03 & 0.03 & 0.07 & 0.01 \\
EDAXH12 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 12 & 1 & 1 & 655 & 0.12 & 0.19 & 0.15 & 0.19 & 0.15 & 0.06 & 0.05 & 0.03 & 0.02 & 0.07 & 0.01 \\
EDAXH13 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 13 & 1 & 1 & 655 & 0.12 & 0.20 & 0.16 & 0.19 & 0.15 & 0.07 & 0.05 & 0.03 & 0.02 & 0.07 & 0.01 \\
EDAXH14 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 14 & 1 & 1 & 654 & 0.12 & 0.20 & 0.16 & 0.19 & 0.15 & 0.07 & 0.04 & 0.03 & 0.03 & 0.07 & 0.01 \\
EDAXH15 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 15 & 1 & 1 & 654 & 0.12 & 0.21 & 0.16 & 0.19 & 0.15 & 0.07 & 0.04 & 0.03 & 0.03 & 0.07 & 0.01 \\
EDAXH16 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 16 & 1 & 1 & 645 & 0.12 & 0.21 & 0.16 & 0.19 & 0.15 & 0.08 & 0.04 & 0.03 & 0.03 & 0.07 & 0.01 \\
EDAXH17 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 17 & 1 & 1 & 644 & 0.12 & 0.21 & 0.16 & 0.21 & 0.15 & 0.08 & 0.04 & 0.03 & 0.04 & 0.07 & 0.01 \\
EDAXH18 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 18 & 1 & 1 & 640 & 0.12 & 0.21 & 0.17 & 0.23 & 0.20 & 0.08 & 0.04 & 0.03 & 0.04 & 0.07 & 0.01 \\
EDAXH19 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 19 & 1 & 1 & 640 & 0.12 & 0.21 & 0.18 & 0.23 & 0.20 & 0.08 & 0.04 & 0.04 & 0.04 & 0.07 & 0.01 \\
EDAXH20 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 20 & 1 & 1 & 636 & 0.13 & 0.21 & 0.17 & 0.26 & 0.20 & 0.08 & 0.04 & 0.05 & 0.04 & 0.07 & 0.01 \\
EDAXH21 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 21 & 1 & 1 & 633 & 0.13 & 0.22 & 0.17 & 0.26 & 0.20 & 0.09 & 0.04 & 0.05 & 0.04 & 0.07 & 0.01 \\
EDAXH22 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 22 & 1 & 1 & 635 & 0.13 & 0.22 & 0.17 & 0.26 & 0.22 & 0.09 & 0.05 & 0.05 & 0.04 & 0.08 & 0.01 \\
EDAXH23 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 23 & 1 & 1 & 634 & 0.13 & 0.22 & 0.16 & 0.26 & 0.22 & 0.09 & 0.05 & 0.05 & 0.04 & 0.09 & 0.01 \\
EDAXH24 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 24 & 1 & 1 & 634 & 0.13 & 0.22 & 0.16 & 0.23 & 0.22 & 0.09 & 0.04 & 0.05 & 0.04 & 0.09 & 0.01 \\
EDAXH25 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 25 & 1 & 1 & 629 & 0.13 & 0.23 & 0.16 & 0.21 & 0.25 & 0.09 & 0.04 & 0.06 & 0.04 & 0.08 & 0.01 \\
EDAXH26 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 26 & 1 & 1 & 622 & 0.13 & 0.23 & 0.17 & 0.21 & 0.22 & 0.10 & 0.04 & 0.07 & 0.04 & 0.08 & 0.01 \\
EDAXH27 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 27 & 1 & 1 & 619 & 0.13 & 0.23 & 0.18 & 0.21 & 0.22 & 0.10 & 0.05 & 0.07 & 0.04 & 0.08 & 0.01 \\
EDAXH28 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 28 & 1 & 1 & 620 & 0.14 & 0.23 & 0.18 & 0.26 & 0.22 & 0.10 & 0.05 & 0.07 & 0.04 & 0.08 & 0.01 \\
EDAXH29 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 29 & 1 & 1 & 616 & 0.14 & 0.23 & 0.19 & 0.26 & 0.22 & 0.11 & 0.05 & 0.07 & 0.04 & 0.08 & 0.01 \\
EDAXH30 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 30 & 1 & 1 & 610 & 0.14 & 0.23 & 0.18 & 0.26 & 0.22 & 0.11 & 0.05 & 0.06 & 0.04 & 0.08 & 0.01 \\
EDAXH31 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 31 & 1 & 1 & 603 & 0.14 & 0.22 & 0.18 & 0.28 & 0.22 & 0.11 & 0.05 & 0.06 & 0.05 & 0.08 & 0.01 \\
EDAXH32 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 32 & 1 & 1 & 597 & 0.14 & 0.22 & 0.18 & 0.28 & 0.22 & 0.11 & 0.05 & 0.06 & 0.05 & 0.08 & 0.02 \\
EDAXH33 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 33 & 1 & 1 & 598 & 0.14 & 0.22 & 0.18 & 0.26 & 0.22 & 0.11 & 0.06 & 0.06 & 0.05 & 0.08 & 0.02 \\
EDAXH34 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 34 & 1 & 1 & 596 & 0.14 & 0.22 & 0.18 & 0.26 & 0.22 & 0.11 & 0.06 & 0.07 & 0.05 & 0.09 & 0.02 \\
EDAXH35 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 35 & 1 & 1 & 592 & 0.14 & 0.22 & 0.19 & 0.26 & 0.22 & 0.11 & 0.06 & 0.07 & 0.06 & 0.08 & 0.02 \\
EDAXH36 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 36 & 1 & 1 & 590 & 0.15 & 0.22 & 0.19 & 0.26 & 0.25 & 0.11 & 0.06 & 0.07 & 0.06 & 0.08 & 0.02 \\
EDAXH37 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 37 & 1 & 1 & 587 & 0.15 & 0.22 & 0.19 & 0.26 & 0.25 & 0.11 & 0.06 & 0.06 & 0.06 & 0.08 & 0.02 \\
EDAXH38 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 38 & 1 & 1 & 588 & 0.15 & 0.22 & 0.18 & 0.26 & 0.25 & 0.12 & 0.06 & 0.05 & 0.06 & 0.08 & 0.02 \\
EDAXH39 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 39 & 1 & 1 & 588 & 0.15 & 0.22 & 0.17 & 0.26 & 0.25 & 0.12 & 0.05 & 0.05 & 0.06 & 0.08 & 0.02 \\
EDAXH40 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 40 & 1 & 1 & 587 & 0.15 & 0.22 & 0.16 & 0.23 & 0.22 & 0.12 & 0.05 & 0.05 & 0.06 & 0.08 & 0.02 \\
EDAXH41 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 41 & 1 & 1 & 584 & 0.15 & 0.22 & 0.16 & 0.23 & 0.22 & 0.12 & 0.06 & 0.06 & 0.06 & 0.07 & 0.02 \\
EDAXH42 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 42 & 1 & 1 & 579 & 0.15 & 0.21 & 0.17 & 0.23 & 0.20 & 0.12 & 0.06 & 0.06 & 0.07 & 0.08 & 0.02 \\
EDAXH43 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 43 & 1 & 1 & 575 & 0.15 & 0.21 & 0.18 & 0.23 & 0.22 & 0.12 & 0.06 & 0.06 & 0.07 & 0.08 & 0.02 \\
EDAXH44 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 44 & 1 & 1 & 570 & 0.15 & 0.21 & 0.17 & 0.23 & 0.22 & 0.12 & 0.06 & 0.05 & 0.07 & 0.08 & 0.02 \\
EDAXH45 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 45 & 1 & 1 & 566 & 0.15 & 0.21 & 0.18 & 0.23 & 0.20 & 0.12 & 0.06 & 0.05 & 0.07 & 0.08 & 0.02 \\
EDAXH46 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 46 & 1 & 1 & 563 & 0.15 & 0.21 & 0.18 & 0.21 & 0.20 & 0.13 & 0.06 & 0.05 & 0.07 & 0.09 & 0.02 \\
EDAXH47 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 47 & 1 & 1 & 557 & 0.15 & 0.21 & 0.19 & 0.21 & 0.18 & 0.13 & 0.06 & 0.05 & 0.07 & 0.09 & 0.03 \\
EDAXH48 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 48 & 1 & 1 & 550 & 0.15 & 0.21 & 0.18 & 0.21 & 0.18 & 0.13 & 0.06 & 0.05 & 0.07 & 0.09 & 0.02 \\
EDAXH49 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 49 & 1 & 1 & 549 & 0.15 & 0.21 & 0.19 & 0.21 & 0.18 & 0.14 & 0.05 & 0.05 & 0.08 & 0.09 & 0.03 \\
EDAXH50 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 50 & 1 & 1 & 541 & 0.15 & 0.21 & 0.19 & 0.23 & 0.18 & 0.15 & 0.05 & 0.05 & 0.08 & 0.08 & 0.03 \\
EDAXH51 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 51 & 1 & 1 & 542 & 0.15 & 0.21 & 0.19 & 0.23 & 0.18 & 0.15 & 0.05 & 0.05 & 0.08 & 0.07 & 0.02 \\
EDAXH52 & IN ACADEMICS IN NON-JC PRGRMS IN WEEK 52 & 1 & 1 & 539 & 0.15 & 0.20 & 0.20 & 0.23 & 0.18 & 0.14 & 0.04 & 0.05 & 0.08 & 0.07 & 0.02 \\
DGTRH1 & IN A DRUG TREATMENT PRGRM IN WEEK 1 & 1 & 1 & 267 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH2 & IN A DRUG TREATMENT PRGRM IN WEEK 2 & 1 & 1 & 267 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH3 & IN A DRUG TREATMENT PRGRM IN WEEK 3 & 1 & 1 & 267 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH4 & IN A DRUG TREATMENT PRGRM IN WEEK 4 & 1 & 1 & 267 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 \\
DGTRH5 & IN A DRUG TREATMENT PRGRM IN WEEK 5 & 1 & 1 & 267 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 \\
DGTRH6 & IN A DRUG TREATMENT PRGRM IN WEEK 6 & 1 & 1 & 267 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH7 & IN A DRUG TREATMENT PRGRM IN WEEK 7 & 1 & 1 & 267 & 0.00 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH8 & IN A DRUG TREATMENT PRGRM IN WEEK 8 & 1 & 1 & 267 & 0.00 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH9 & IN A DRUG TREATMENT PRGRM IN WEEK 9 & 1 & 1 & 267 & 0.00 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH10 & IN A DRUG TREATMENT PRGRM IN WEEK 10 & 1 & 1 & 267 & 0.00 & 0.01 & 0.00 & 0.00 & 0.02 & 0.00 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH11 & IN A DRUG TREATMENT PRGRM IN WEEK 11 & 1 & 1 & 267 & 0.01 & 0.01 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH12 & IN A DRUG TREATMENT PRGRM IN WEEK 12 & 1 & 1 & 267 & 0.00 & 0.01 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 \\
DGTRH13 & IN A DRUG TREATMENT PRGRM IN WEEK 13 & 1 & 1 & 23 & 0.00 & 0.01 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 \\
DGTRH14 & IN A DRUG TREATMENT PRGRM IN WEEK 14 & 1 & 1 & 23 & 0.00 & 0.01 & 0.00 & 0.00 & 0.02 & 0.00 & 0.01 & 0.00 & 0.01 & 0.00 & 0.00 \\
DGTRH15 & IN A DRUG TREATMENT PRGRM IN WEEK 15 & 1 & 1 & 23 & 0.00 & 0.01 & 0.00 & 0.00 & 0.02 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH16 & IN A DRUG TREATMENT PRGRM IN WEEK 16 & 1 & 1 & 23 & 0.01 & 0.01 & 0.00 & 0.00 & 0.02 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH17 & IN A DRUG TREATMENT PRGRM IN WEEK 17 & 1 & 1 & 23 & 0.01 & 0.01 & 0.01 & 0.00 & 0.02 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH18 & IN A DRUG TREATMENT PRGRM IN WEEK 18 & 1 & 1 & 23 & 0.00 & 0.01 & 0.01 & 0.00 & 0.02 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH19 & IN A DRUG TREATMENT PRGRM IN WEEK 19 & 1 & 1 & 23 & 0.00 & 0.01 & 0.01 & 0.00 & 0.02 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH20 & IN A DRUG TREATMENT PRGRM IN WEEK 20 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH21 & IN A DRUG TREATMENT PRGRM IN WEEK 21 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH22 & IN A DRUG TREATMENT PRGRM IN WEEK 22 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
DGTRH23 & IN A DRUG TREATMENT PRGRM IN WEEK 23 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH24 & IN A DRUG TREATMENT PRGRM IN WEEK 24 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH25 & IN A DRUG TREATMENT PRGRM IN WEEK 25 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH26 & IN A DRUG TREATMENT PRGRM IN WEEK 26 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH27 & IN A DRUG TREATMENT PRGRM IN WEEK 27 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
DGTRH28 & IN A DRUG TREATMENT PRGRM IN WEEK 28 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
DGTRH29 & IN A DRUG TREATMENT PRGRM IN WEEK 29 & 1 & 1 & 23 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
DGTRH30 & IN A DRUG TREATMENT PRGRM IN WEEK 30 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH31 & IN A DRUG TREATMENT PRGRM IN WEEK 31 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
DGTRH32 & IN A DRUG TREATMENT PRGRM IN WEEK 32 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 \\
DGTRH33 & IN A DRUG TREATMENT PRGRM IN WEEK 33 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
DGTRH34 & IN A DRUG TREATMENT PRGRM IN WEEK 34 & 1 & 1 & 23 & 0.01 & 0.01 & 0.01 & 0.00 & 0.05 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
DGTRH35 & IN A DRUG TREATMENT PRGRM IN WEEK 35 & 1 & 1 & 23 & 0.01 & 0.01 & 0.01 & 0.00 & 0.05 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
DGTRH36 & IN A DRUG TREATMENT PRGRM IN WEEK 36 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.05 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
DGTRH37 & IN A DRUG TREATMENT PRGRM IN WEEK 37 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
DGTRH38 & IN A DRUG TREATMENT PRGRM IN WEEK 38 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH39 & IN A DRUG TREATMENT PRGRM IN WEEK 39 & 1 & 1 & 25 & 0.01 & 0.01 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH40 & IN A DRUG TREATMENT PRGRM IN WEEK 40 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH41 & IN A DRUG TREATMENT PRGRM IN WEEK 41 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH42 & IN A DRUG TREATMENT PRGRM IN WEEK 42 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH43 & IN A DRUG TREATMENT PRGRM IN WEEK 43 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH44 & IN A DRUG TREATMENT PRGRM IN WEEK 44 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH45 & IN A DRUG TREATMENT PRGRM IN WEEK 45 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH46 & IN A DRUG TREATMENT PRGRM IN WEEK 46 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH47 & IN A DRUG TREATMENT PRGRM IN WEEK 47 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH48 & IN A DRUG TREATMENT PRGRM IN WEEK 48 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH49 & IN A DRUG TREATMENT PRGRM IN WEEK 49 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH50 & IN A DRUG TREATMENT PRGRM IN WEEK 50 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH51 & IN A DRUG TREATMENT PRGRM IN WEEK 51 & 1 & 1 & 26 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
DGTRH52 & IN A DRUG TREATMENT PRGRM IN WEEK 52 & 1 & 1 & 27 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
WORKH1 & EMPLOYMENT STATUS IN WEEK 1 & 1 & 1 & 521 & 0.24 & 0.22 & 0.26 & 0.17 & 0.26 & 0.20 & 0.20 & 0.20 & 0.21 & 0.17 & 0.21 \\
WORKH2 & EMPLOYMENT STATUS IN WEEK 2 & 1 & 1 & 574 & 0.24 & 0.23 & 0.23 & 0.12 & 0.26 & 0.16 & 0.15 & 0.17 & 0.18 & 0.14 & 0.18 \\
WORKH3 & EMPLOYMENT STATUS IN WEEK 3 & 1 & 1 & 571 & 0.24 & 0.25 & 0.22 & 0.10 & 0.26 & 0.14 & 0.13 & 0.15 & 0.15 & 0.10 & 0.15 \\
WORKH4 & EMPLOYMENT STATUS IN WEEK 4 & 1 & 1 & 578 & 0.24 & 0.26 & 0.23 & 0.12 & 0.26 & 0.14 & 0.12 & 0.11 & 0.13 & 0.06 & 0.12 \\
WORKH5 & EMPLOYMENT STATUS IN WEEK 5 & 1 & 1 & 580 & 0.25 & 0.27 & 0.23 & 0.12 & 0.26 & 0.13 & 0.11 & 0.11 & 0.12 & 0.07 & 0.10 \\
WORKH6 & EMPLOYMENT STATUS IN WEEK 6 & 1 & 1 & 585 & 0.26 & 0.28 & 0.24 & 0.14 & 0.31 & 0.12 & 0.09 & 0.11 & 0.10 & 0.05 & 0.08 \\
WORKH7 & EMPLOYMENT STATUS IN WEEK 7 & 1 & 1 & 586 & 0.27 & 0.29 & 0.26 & 0.12 & 0.33 & 0.13 & 0.09 & 0.10 & 0.10 & 0.07 & 0.07 \\
WORKH8 & EMPLOYMENT STATUS IN WEEK 8 & 1 & 1 & 585 & 0.27 & 0.30 & 0.27 & 0.12 & 0.31 & 0.14 & 0.09 & 0.09 & 0.11 & 0.07 & 0.08 \\
WORKH9 & EMPLOYMENT STATUS IN WEEK 9 & 1 & 1 & 587 & 0.28 & 0.31 & 0.27 & 0.12 & 0.31 & 0.14 & 0.09 & 0.09 & 0.11 & 0.06 & 0.08 \\
WORKH10 & EMPLOYMENT STATUS IN WEEK 10 & 1 & 1 & 584 & 0.29 & 0.31 & 0.28 & 0.14 & 0.31 & 0.15 & 0.08 & 0.10 & 0.11 & 0.06 & 0.08 \\
WORKH11 & EMPLOYMENT STATUS IN WEEK 11 & 1 & 1 & 582 & 0.29 & 0.32 & 0.29 & 0.14 & 0.36 & 0.15 & 0.09 & 0.09 & 0.12 & 0.06 & 0.08 \\
WORKH12 & EMPLOYMENT STATUS IN WEEK 12 & 1 & 1 & 587 & 0.30 & 0.33 & 0.30 & 0.12 & 0.36 & 0.16 & 0.08 & 0.09 & 0.12 & 0.08 & 0.08 \\
WORKH13 & EMPLOYMENT STATUS IN WEEK 13 & 1 & 1 & 585 & 0.30 & 0.33 & 0.33 & 0.10 & 0.36 & 0.17 & 0.09 & 0.09 & 0.13 & 0.08 & 0.08 \\
WORKH14 & EMPLOYMENT STATUS IN WEEK 14 & 1 & 1 & 588 & 0.31 & 0.34 & 0.33 & 0.10 & 0.33 & 0.18 & 0.09 & 0.10 & 0.13 & 0.10 & 0.07 \\
WORKH15 & EMPLOYMENT STATUS IN WEEK 15 & 1 & 1 & 583 & 0.31 & 0.34 & 0.34 & 0.12 & 0.31 & 0.19 & 0.09 & 0.09 & 0.13 & 0.10 & 0.08 \\
WORKH16 & EMPLOYMENT STATUS IN WEEK 16 & 1 & 1 & 582 & 0.31 & 0.35 & 0.33 & 0.12 & 0.31 & 0.19 & 0.10 & 0.09 & 0.14 & 0.10 & 0.08 \\
WORKH17 & EMPLOYMENT STATUS IN WEEK 17 & 1 & 1 & 585 & 0.32 & 0.35 & 0.35 & 0.10 & 0.31 & 0.20 & 0.10 & 0.09 & 0.14 & 0.10 & 0.08 \\
WORKH18 & EMPLOYMENT STATUS IN WEEK 18 & 1 & 1 & 586 & 0.33 & 0.35 & 0.34 & 0.12 & 0.33 & 0.21 & 0.11 & 0.10 & 0.16 & 0.10 & 0.08 \\
WORKH19 & EMPLOYMENT STATUS IN WEEK 19 & 1 & 1 & 581 & 0.33 & 0.36 & 0.35 & 0.14 & 0.33 & 0.22 & 0.12 & 0.10 & 0.16 & 0.10 & 0.08 \\
WORKH20 & EMPLOYMENT STATUS IN WEEK 20 & 1 & 1 & 579 & 0.33 & 0.37 & 0.34 & 0.12 & 0.36 & 0.23 & 0.12 & 0.11 & 0.18 & 0.10 & 0.08 \\
WORKH21 & EMPLOYMENT STATUS IN WEEK 21 & 1 & 1 & 579 & 0.34 & 0.37 & 0.36 & 0.12 & 0.36 & 0.24 & 0.12 & 0.11 & 0.19 & 0.11 & 0.08 \\
WORKH22 & EMPLOYMENT STATUS IN WEEK 22 & 1 & 1 & 576 & 0.35 & 0.37 & 0.36 & 0.12 & 0.38 & 0.24 & 0.13 & 0.11 & 0.20 & 0.12 & 0.08 \\
WORKH23 & EMPLOYMENT STATUS IN WEEK 23 & 1 & 1 & 577 & 0.35 & 0.37 & 0.38 & 0.10 & 0.33 & 0.25 & 0.13 & 0.12 & 0.20 & 0.13 & 0.09 \\
WORKH24 & EMPLOYMENT STATUS IN WEEK 24 & 1 & 1 & 568 & 0.36 & 0.38 & 0.38 & 0.12 & 0.36 & 0.26 & 0.14 & 0.12 & 0.21 & 0.13 & 0.10 \\
WORKH25 & EMPLOYMENT STATUS IN WEEK 25 & 1 & 1 & 568 & 0.36 & 0.38 & 0.38 & 0.17 & 0.36 & 0.27 & 0.15 & 0.11 & 0.21 & 0.13 & 0.09 \\
WORKH26 & EMPLOYMENT STATUS IN WEEK 26 & 1 & 1 & 561 & 0.37 & 0.38 & 0.37 & 0.17 & 0.33 & 0.28 & 0.14 & 0.11 & 0.23 & 0.13 & 0.10 \\
WORKH27 & EMPLOYMENT STATUS IN WEEK 27 & 1 & 1 & 554 & 0.38 & 0.39 & 0.37 & 0.19 & 0.31 & 0.28 & 0.14 & 0.12 & 0.24 & 0.15 & 0.11 \\
WORKH28 & EMPLOYMENT STATUS IN WEEK 28 & 1 & 1 & 550 & 0.38 & 0.39 & 0.38 & 0.24 & 0.33 & 0.29 & 0.15 & 0.11 & 0.25 & 0.15 & 0.11 \\
WORKH29 & EMPLOYMENT STATUS IN WEEK 29 & 1 & 1 & 550 & 0.39 & 0.39 & 0.39 & 0.24 & 0.33 & 0.29 & 0.15 & 0.12 & 0.26 & 0.13 & 0.11 \\
WORKH30 & EMPLOYMENT STATUS IN WEEK 30 & 1 & 1 & 551 & 0.39 & 0.39 & 0.39 & 0.24 & 0.38 & 0.30 & 0.16 & 0.13 & 0.27 & 0.14 & 0.11 \\
WORKH31 & EMPLOYMENT STATUS IN WEEK 31 & 1 & 1 & 545 & 0.39 & 0.40 & 0.39 & 0.26 & 0.40 & 0.31 & 0.17 & 0.13 & 0.27 & 0.16 & 0.12 \\
WORKH32 & EMPLOYMENT STATUS IN WEEK 32 & 1 & 1 & 545 & 0.39 & 0.40 & 0.40 & 0.24 & 0.43 & 0.31 & 0.16 & 0.15 & 0.28 & 0.18 & 0.12 \\
WORKH33 & EMPLOYMENT STATUS IN WEEK 33 & 1 & 1 & 543 & 0.40 & 0.41 & 0.40 & 0.26 & 0.43 & 0.32 & 0.17 & 0.14 & 0.29 & 0.19 & 0.12 \\
WORKH34 & EMPLOYMENT STATUS IN WEEK 34 & 1 & 1 & 536 & 0.39 & 0.41 & 0.38 & 0.26 & 0.45 & 0.31 & 0.16 & 0.14 & 0.30 & 0.17 & 0.12 \\
WORKH35 & EMPLOYMENT STATUS IN WEEK 35 & 1 & 1 & 531 & 0.39 & 0.41 & 0.40 & 0.29 & 0.40 & 0.32 & 0.17 & 0.14 & 0.32 & 0.21 & 0.13 \\
WORKH36 & EMPLOYMENT STATUS IN WEEK 36 & 1 & 1 & 517 & 0.40 & 0.42 & 0.43 & 0.26 & 0.38 & 0.32 & 0.16 & 0.15 & 0.33 & 0.20 & 0.13 \\
WORKH37 & EMPLOYMENT STATUS IN WEEK 37 & 1 & 1 & 513 & 0.40 & 0.43 & 0.42 & 0.24 & 0.36 & 0.33 & 0.15 & 0.15 & 0.35 & 0.21 & 0.14 \\
WORKH38 & EMPLOYMENT STATUS IN WEEK 38 & 1 & 1 & 511 & 0.40 & 0.43 & 0.42 & 0.24 & 0.36 & 0.33 & 0.15 & 0.16 & 0.36 & 0.19 & 0.14 \\
WORKH39 & EMPLOYMENT STATUS IN WEEK 39 & 1 & 1 & 509 & 0.41 & 0.43 & 0.42 & 0.26 & 0.34 & 0.33 & 0.15 & 0.17 & 0.37 & 0.18 & 0.14 \\
WORKH40 & EMPLOYMENT STATUS IN WEEK 40 & 1 & 1 & 498 & 0.42 & 0.43 & 0.43 & 0.26 & 0.32 & 0.34 & 0.16 & 0.17 & 0.37 & 0.17 & 0.14 \\
WORKH41 & EMPLOYMENT STATUS IN WEEK 41 & 1 & 1 & 497 & 0.41 & 0.43 & 0.42 & 0.23 & 0.27 & 0.34 & 0.15 & 0.15 & 0.38 & 0.17 & 0.15 \\
WORKH42 & EMPLOYMENT STATUS IN WEEK 42 & 1 & 1 & 487 & 0.41 & 0.43 & 0.42 & 0.23 & 0.20 & 0.35 & 0.15 & 0.15 & 0.39 & 0.17 & 0.15 \\
WORKH43 & EMPLOYMENT STATUS IN WEEK 43 & 1 & 1 & 476 & 0.42 & 0.44 & 0.42 & 0.26 & 0.27 & 0.36 & 0.16 & 0.14 & 0.41 & 0.17 & 0.15 \\
WORKH44 & EMPLOYMENT STATUS IN WEEK 44 & 1 & 1 & 477 & 0.42 & 0.44 & 0.42 & 0.28 & 0.27 & 0.36 & 0.16 & 0.14 & 0.42 & 0.17 & 0.15 \\
WORKH45 & EMPLOYMENT STATUS IN WEEK 45 & 1 & 1 & 472 & 0.42 & 0.44 & 0.41 & 0.28 & 0.27 & 0.38 & 0.17 & 0.12 & 0.44 & 0.17 & 0.15 \\
WORKH46 & EMPLOYMENT STATUS IN WEEK 46 & 1 & 1 & 464 & 0.41 & 0.44 & 0.42 & 0.30 & 0.24 & 0.38 & 0.17 & 0.13 & 0.46 & 0.19 & 0.15 \\
WORKH47 & EMPLOYMENT STATUS IN WEEK 47 & 1 & 1 & 451 & 0.42 & 0.44 & 0.42 & 0.30 & 0.24 & 0.38 & 0.18 & 0.13 & 0.46 & 0.16 & 0.15 \\
WORKH48 & EMPLOYMENT STATUS IN WEEK 48 & 1 & 1 & 444 & 0.42 & 0.44 & 0.42 & 0.30 & 0.20 & 0.39 & 0.20 & 0.14 & 0.46 & 0.17 & 0.15 \\
WORKH49 & EMPLOYMENT STATUS IN WEEK 49 & 1 & 1 & 436 & 0.42 & 0.44 & 0.42 & 0.33 & 0.20 & 0.38 & 0.19 & 0.14 & 0.47 & 0.18 & 0.15 \\
WORKH50 & EMPLOYMENT STATUS IN WEEK 50 & 1 & 1 & 425 & 0.43 & 0.44 & 0.42 & 0.28 & 0.17 & 0.38 & 0.18 & 0.14 & 0.48 & 0.18 & 0.16 \\
WORKH51 & EMPLOYMENT STATUS IN WEEK 51 & 1 & 1 & 421 & 0.43 & 0.44 & 0.42 & 0.28 & 0.20 & 0.38 & 0.19 & 0.13 & 0.48 & 0.19 & 0.16 \\
WORKH52 & EMPLOYMENT STATUS IN WEEK 52 & 1 & 1 & 417 & 0.43 & 0.44 & 0.41 & 0.26 & 0.17 & 0.38 & 0.19 & 0.13 & 0.49 & 0.21 & 0.16 \\
CCEMP1 & USED CHILD CARE WHILE EMPLOYED IN WEEK 1 & 1 & 1 & 10 & 0.03 & 0.03 & 0.04 & 0.05 & 0.07 & 0.02 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
CCEMP2 & USED CHILD CARE WHILE EMPLOYED IN WEEK 2 & 1 & 1 & 9 & 0.04 & 0.03 & 0.04 & 0.05 & 0.07 & 0.02 & 0.01 & 0.02 & 0.02 & 0.00 & 0.01 \\
CCEMP3 & USED CHILD CARE WHILE EMPLOYED IN WEEK 3 & 1 & 1 & 9 & 0.04 & 0.04 & 0.04 & 0.05 & 0.10 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 \\
CCEMP4 & USED CHILD CARE WHILE EMPLOYED IN WEEK 4 & 1 & 1 & 9 & 0.05 & 0.04 & 0.04 & 0.05 & 0.10 & 0.02 & 0.02 & 0.02 & 0.02 & 0.00 & 0.01 \\
CCEMP5 & USED CHILD CARE WHILE EMPLOYED IN WEEK 5 & 1 & 1 & 9 & 0.05 & 0.04 & 0.04 & 0.05 & 0.10 & 0.02 & 0.02 & 0.02 & 0.02 & 0.01 & 0.01 \\
CCEMP6 & USED CHILD CARE WHILE EMPLOYED IN WEEK 6 & 1 & 1 & 8 & 0.06 & 0.05 & 0.05 & 0.05 & 0.12 & 0.02 & 0.02 & 0.02 & 0.02 & 0.01 & 0.01 \\
CCEMP7 & USED CHILD CARE WHILE EMPLOYED IN WEEK 7 & 1 & 1 & 8 & 0.06 & 0.05 & 0.05 & 0.05 & 0.12 & 0.02 & 0.02 & 0.02 & 0.02 & 0.02 & 0.01 \\
CCEMP8 & USED CHILD CARE WHILE EMPLOYED IN WEEK 8 & 1 & 1 & 9 & 0.06 & 0.05 & 0.05 & 0.05 & 0.10 & 0.03 & 0.03 & 0.02 & 0.02 & 0.02 & 0.01 \\
CCEMP9 & USED CHILD CARE WHILE EMPLOYED IN WEEK 9 & 1 & 1 & 9 & 0.06 & 0.05 & 0.05 & 0.05 & 0.10 & 0.03 & 0.02 & 0.02 & 0.02 & 0.02 & 0.01 \\
CCEMP10 & USED CHILD CARE WHILE EMPLOYED IN WEEK 10 & 1 & 1 & 9 & 0.06 & 0.05 & 0.06 & 0.05 & 0.10 & 0.03 & 0.02 & 0.02 & 0.02 & 0.01 & 0.01 \\
CCEMP11 & USED CHILD CARE WHILE EMPLOYED IN WEEK 11 & 1 & 1 & 9 & 0.06 & 0.06 & 0.06 & 0.05 & 0.12 & 0.03 & 0.03 & 0.02 & 0.02 & 0.01 & 0.01 \\
CCEMP12 & USED CHILD CARE WHILE EMPLOYED IN WEEK 12 & 1 & 1 & 11 & 0.06 & 0.06 & 0.07 & 0.02 & 0.12 & 0.03 & 0.02 & 0.02 & 0.03 & 0.01 & 0.01 \\
CCEMP13 & USED CHILD CARE WHILE EMPLOYED IN WEEK 13 & 1 & 1 & 12 & 0.07 & 0.06 & 0.07 & 0.02 & 0.12 & 0.04 & 0.02 & 0.02 & 0.03 & 0.02 & 0.01 \\
CCEMP14 & USED CHILD CARE WHILE EMPLOYED IN WEEK 14 & 1 & 1 & 13 & 0.07 & 0.06 & 0.07 & 0.02 & 0.12 & 0.04 & 0.02 & 0.02 & 0.03 & 0.02 & 0.01 \\
CCEMP15 & USED CHILD CARE WHILE EMPLOYED IN WEEK 15 & 1 & 1 & 13 & 0.07 & 0.06 & 0.08 & 0.02 & 0.12 & 0.04 & 0.02 & 0.02 & 0.03 & 0.02 & 0.01 \\
CCEMP16 & USED CHILD CARE WHILE EMPLOYED IN WEEK 16 & 1 & 1 & 13 & 0.07 & 0.06 & 0.07 & 0.02 & 0.12 & 0.05 & 0.02 & 0.02 & 0.03 & 0.03 & 0.01 \\
CCEMP17 & USED CHILD CARE WHILE EMPLOYED IN WEEK 17 & 1 & 1 & 13 & 0.08 & 0.06 & 0.08 & 0.02 & 0.10 & 0.05 & 0.02 & 0.02 & 0.03 & 0.02 & 0.01 \\
CCEMP18 & USED CHILD CARE WHILE EMPLOYED IN WEEK 18 & 1 & 1 & 13 & 0.08 & 0.06 & 0.08 & 0.05 & 0.12 & 0.05 & 0.02 & 0.03 & 0.04 & 0.02 & 0.01 \\
CCEMP19 & USED CHILD CARE WHILE EMPLOYED IN WEEK 19 & 1 & 1 & 13 & 0.08 & 0.06 & 0.08 & 0.05 & 0.12 & 0.05 & 0.03 & 0.03 & 0.04 & 0.02 & 0.01 \\
CCEMP20 & USED CHILD CARE WHILE EMPLOYED IN WEEK 20 & 1 & 1 & 15 & 0.08 & 0.07 & 0.08 & 0.05 & 0.14 & 0.05 & 0.03 & 0.03 & 0.04 & 0.02 & 0.01 \\
CCEMP21 & USED CHILD CARE WHILE EMPLOYED IN WEEK 21 & 1 & 1 & 15 & 0.08 & 0.07 & 0.08 & 0.05 & 0.12 & 0.05 & 0.03 & 0.03 & 0.04 & 0.02 & 0.01 \\
CCEMP22 & USED CHILD CARE WHILE EMPLOYED IN WEEK 22 & 1 & 1 & 15 & 0.09 & 0.07 & 0.08 & 0.05 & 0.14 & 0.05 & 0.03 & 0.03 & 0.04 & 0.03 & 0.01 \\
CCEMP23 & USED CHILD CARE WHILE EMPLOYED IN WEEK 23 & 1 & 1 & 15 & 0.09 & 0.07 & 0.09 & 0.05 & 0.10 & 0.06 & 0.03 & 0.03 & 0.04 & 0.03 & 0.01 \\
CCEMP24 & USED CHILD CARE WHILE EMPLOYED IN WEEK 24 & 1 & 1 & 15 & 0.09 & 0.07 & 0.09 & 0.05 & 0.12 & 0.06 & 0.03 & 0.04 & 0.05 & 0.03 & 0.01 \\
CCEMP25 & USED CHILD CARE WHILE EMPLOYED IN WEEK 25 & 1 & 1 & 15 & 0.09 & 0.07 & 0.09 & 0.07 & 0.12 & 0.06 & 0.04 & 0.03 & 0.05 & 0.03 & 0.01 \\
CCEMP26 & USED CHILD CARE WHILE EMPLOYED IN WEEK 26 & 1 & 1 & 15 & 0.09 & 0.07 & 0.08 & 0.07 & 0.10 & 0.06 & 0.03 & 0.03 & 0.05 & 0.03 & 0.01 \\
CCEMP27 & USED CHILD CARE WHILE EMPLOYED IN WEEK 27 & 1 & 1 & 15 & 0.09 & 0.07 & 0.08 & 0.07 & 0.10 & 0.06 & 0.03 & 0.03 & 0.06 & 0.04 & 0.01 \\
CCEMP28 & USED CHILD CARE WHILE EMPLOYED IN WEEK 28 & 1 & 1 & 15 & 0.09 & 0.07 & 0.08 & 0.12 & 0.12 & 0.06 & 0.04 & 0.03 & 0.06 & 0.04 & 0.02 \\
CCEMP29 & USED CHILD CARE WHILE EMPLOYED IN WEEK 29 & 1 & 1 & 15 & 0.10 & 0.07 & 0.08 & 0.09 & 0.12 & 0.06 & 0.03 & 0.04 & 0.06 & 0.03 & 0.02 \\
CCEMP30 & USED CHILD CARE WHILE EMPLOYED IN WEEK 30 & 1 & 1 & 15 & 0.10 & 0.08 & 0.08 & 0.09 & 0.12 & 0.06 & 0.03 & 0.05 & 0.06 & 0.03 & 0.02 \\
CCEMP31 & USED CHILD CARE WHILE EMPLOYED IN WEEK 31 & 1 & 1 & 15 & 0.10 & 0.08 & 0.08 & 0.09 & 0.12 & 0.06 & 0.03 & 0.05 & 0.06 & 0.04 & 0.02 \\
CCEMP32 & USED CHILD CARE WHILE EMPLOYED IN WEEK 32 & 1 & 1 & 15 & 0.10 & 0.08 & 0.08 & 0.09 & 0.14 & 0.06 & 0.03 & 0.06 & 0.06 & 0.04 & 0.02 \\
CCEMP33 & USED CHILD CARE WHILE EMPLOYED IN WEEK 33 & 1 & 1 & 14 & 0.10 & 0.08 & 0.08 & 0.12 & 0.14 & 0.06 & 0.03 & 0.05 & 0.06 & 0.04 & 0.02 \\
CCEMP34 & USED CHILD CARE WHILE EMPLOYED IN WEEK 34 & 1 & 1 & 12 & 0.10 & 0.08 & 0.08 & 0.12 & 0.14 & 0.06 & 0.03 & 0.05 & 0.06 & 0.04 & 0.03 \\
CCEMP35 & USED CHILD CARE WHILE EMPLOYED IN WEEK 35 & 1 & 1 & 12 & 0.10 & 0.08 & 0.08 & 0.14 & 0.14 & 0.06 & 0.03 & 0.05 & 0.06 & 0.04 & 0.03 \\
CCEMP36 & USED CHILD CARE WHILE EMPLOYED IN WEEK 36 & 1 & 1 & 12 & 0.10 & 0.08 & 0.08 & 0.12 & 0.12 & 0.07 & 0.03 & 0.05 & 0.07 & 0.04 & 0.03 \\
CCEMP37 & USED CHILD CARE WHILE EMPLOYED IN WEEK 37 & 1 & 1 & 12 & 0.10 & 0.08 & 0.08 & 0.09 & 0.12 & 0.07 & 0.03 & 0.05 & 0.08 & 0.05 & 0.03 \\
CCEMP38 & USED CHILD CARE WHILE EMPLOYED IN WEEK 38 & 1 & 1 & 11 & 0.10 & 0.08 & 0.08 & 0.09 & 0.12 & 0.07 & 0.03 & 0.05 & 0.08 & 0.04 & 0.03 \\
CCEMP39 & USED CHILD CARE WHILE EMPLOYED IN WEEK 39 & 1 & 1 & 12 & 0.10 & 0.08 & 0.08 & 0.12 & 0.12 & 0.07 & 0.03 & 0.05 & 0.08 & 0.03 & 0.03 \\
CCEMP40 & USED CHILD CARE WHILE EMPLOYED IN WEEK 40 & 1 & 1 & 12 & 0.10 & 0.08 & 0.09 & 0.12 & 0.10 & 0.07 & 0.04 & 0.06 & 0.08 & 0.02 & 0.03 \\
CCEMP41 & USED CHILD CARE WHILE EMPLOYED IN WEEK 41 & 1 & 1 & 11 & 0.10 & 0.08 & 0.09 & 0.12 & 0.07 & 0.07 & 0.03 & 0.06 & 0.09 & 0.02 & 0.03 \\
CCEMP42 & USED CHILD CARE WHILE EMPLOYED IN WEEK 42 & 1 & 1 & 11 & 0.10 & 0.09 & 0.09 & 0.12 & 0.05 & 0.07 & 0.03 & 0.05 & 0.09 & 0.02 & 0.04 \\
CCEMP43 & USED CHILD CARE WHILE EMPLOYED IN WEEK 43 & 1 & 1 & 10 & 0.11 & 0.09 & 0.10 & 0.12 & 0.07 & 0.08 & 0.03 & 0.05 & 0.09 & 0.02 & 0.04 \\
CCEMP44 & USED CHILD CARE WHILE EMPLOYED IN WEEK 44 & 1 & 1 & 10 & 0.10 & 0.09 & 0.10 & 0.14 & 0.07 & 0.08 & 0.03 & 0.05 & 0.09 & 0.02 & 0.04 \\
CCEMP45 & USED CHILD CARE WHILE EMPLOYED IN WEEK 45 & 1 & 1 & 10 & 0.10 & 0.09 & 0.10 & 0.14 & 0.07 & 0.08 & 0.04 & 0.04 & 0.10 & 0.02 & 0.04 \\
CCEMP46 & USED CHILD CARE WHILE EMPLOYED IN WEEK 46 & 1 & 1 & 9 & 0.11 & 0.09 & 0.10 & 0.14 & 0.05 & 0.08 & 0.04 & 0.04 & 0.10 & 0.02 & 0.03 \\
CCEMP47 & USED CHILD CARE WHILE EMPLOYED IN WEEK 47 & 1 & 1 & 8 & 0.11 & 0.09 & 0.10 & 0.14 & 0.05 & 0.08 & 0.04 & 0.05 & 0.10 & 0.02 & 0.03 \\
CCEMP48 & USED CHILD CARE WHILE EMPLOYED IN WEEK 48 & 1 & 1 & 8 & 0.11 & 0.09 & 0.10 & 0.12 & 0.02 & 0.09 & 0.05 & 0.05 & 0.10 & 0.02 & 0.03 \\
CCEMP49 & USED CHILD CARE WHILE EMPLOYED IN WEEK 49 & 1 & 1 & 8 & 0.11 & 0.09 & 0.10 & 0.12 & 0.02 & 0.08 & 0.05 & 0.05 & 0.11 & 0.01 & 0.03 \\
CCEMP50 & USED CHILD CARE WHILE EMPLOYED IN WEEK 50 & 1 & 1 & 8 & 0.11 & 0.09 & 0.10 & 0.12 & 0.02 & 0.08 & 0.04 & 0.05 & 0.11 & 0.01 & 0.03 \\
CCEMP51 & USED CHILD CARE WHILE EMPLOYED IN WEEK 51 & 1 & 1 & 7 & 0.11 & 0.09 & 0.10 & 0.12 & 0.05 & 0.08 & 0.04 & 0.04 & 0.11 & 0.02 & 0.03 \\
CCEMP52 & USED CHILD CARE WHILE EMPLOYED IN WEEK 52 & 1 & 1 & 8 & 0.11 & 0.09 & 0.10 & 0.12 & 0.02 & 0.08 & 0.04 & 0.04 & 0.11 & 0.02 & 0.03 \\
CCEDT1 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 1 & 1 & 1 & 24 & 0.01 & 0.01 & 0.01 & 0.02 & 0.02 & 0.01 & 0.01 & 0.00 & 0.01 & 0.00 & 0.01 \\
CCEDT2 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 2 & 1 & 1 & 30 & 0.02 & 0.01 & 0.01 & 0.00 & 0.02 & 0.01 & 0.01 & 0.00 & 0.01 & 0.00 & 0.01 \\
CCEDT3 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 3 & 1 & 1 & 33 & 0.02 & 0.02 & 0.01 & 0.02 & 0.02 & 0.01 & 0.01 & 0.00 & 0.01 & 0.00 & 0.00 \\
CCEDT4 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 4 & 1 & 1 & 32 & 0.02 & 0.02 & 0.01 & 0.05 & 0.02 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT5 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 5 & 1 & 1 & 32 & 0.02 & 0.02 & 0.02 & 0.05 & 0.02 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT6 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 6 & 1 & 1 & 32 & 0.02 & 0.02 & 0.02 & 0.05 & 0.02 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT7 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 7 & 1 & 1 & 31 & 0.02 & 0.02 & 0.02 & 0.05 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT8 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 8 & 1 & 1 & 31 & 0.03 & 0.02 & 0.02 & 0.07 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT9 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 9 & 1 & 1 & 31 & 0.03 & 0.02 & 0.02 & 0.07 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT10 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 10 & 1 & 1 & 31 & 0.03 & 0.03 & 0.02 & 0.07 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT11 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 11 & 1 & 1 & 30 & 0.03 & 0.03 & 0.03 & 0.07 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT12 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 12 & 1 & 1 & 28 & 0.03 & 0.03 & 0.03 & 0.07 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT13 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 13 & 1 & 1 & 27 & 0.03 & 0.03 & 0.02 & 0.07 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT14 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 14 & 1 & 1 & 28 & 0.03 & 0.03 & 0.03 & 0.07 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
CCEDT15 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 15 & 1 & 1 & 28 & 0.03 & 0.03 & 0.03 & 0.07 & 0.00 & 0.01 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 \\
CCEDT16 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 16 & 1 & 1 & 27 & 0.03 & 0.03 & 0.03 & 0.05 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
CCEDT17 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 17 & 1 & 1 & 28 & 0.03 & 0.03 & 0.03 & 0.07 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
CCEDT18 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 18 & 1 & 1 & 27 & 0.03 & 0.03 & 0.03 & 0.07 & 0.02 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
CCEDT19 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 19 & 1 & 1 & 27 & 0.03 & 0.03 & 0.03 & 0.07 & 0.02 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
CCEDT20 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 20 & 1 & 1 & 26 & 0.03 & 0.03 & 0.03 & 0.09 & 0.02 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
CCEDT21 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 21 & 1 & 1 & 26 & 0.03 & 0.04 & 0.04 & 0.09 & 0.02 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT22 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 22 & 1 & 1 & 26 & 0.03 & 0.04 & 0.04 & 0.09 & 0.07 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT23 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 23 & 1 & 1 & 26 & 0.03 & 0.04 & 0.04 & 0.09 & 0.07 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT24 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 24 & 1 & 1 & 25 & 0.03 & 0.04 & 0.04 & 0.07 & 0.07 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
CCEDT25 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 25 & 1 & 1 & 24 & 0.03 & 0.04 & 0.04 & 0.07 & 0.07 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
CCEDT26 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 26 & 1 & 1 & 23 & 0.04 & 0.04 & 0.05 & 0.07 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT27 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 27 & 1 & 1 & 23 & 0.04 & 0.04 & 0.05 & 0.07 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT28 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 28 & 1 & 1 & 24 & 0.04 & 0.04 & 0.05 & 0.09 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT29 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 29 & 1 & 1 & 24 & 0.04 & 0.04 & 0.05 & 0.09 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT30 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 30 & 1 & 1 & 23 & 0.04 & 0.04 & 0.05 & 0.09 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT31 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 31 & 1 & 1 & 23 & 0.04 & 0.04 & 0.06 & 0.12 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT32 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 32 & 1 & 1 & 22 & 0.04 & 0.04 & 0.05 & 0.12 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT33 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 33 & 1 & 1 & 21 & 0.04 & 0.04 & 0.05 & 0.09 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT34 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 34 & 1 & 1 & 23 & 0.04 & 0.04 & 0.06 & 0.09 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT35 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 35 & 1 & 1 & 23 & 0.04 & 0.04 & 0.06 & 0.09 & 0.05 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT36 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 36 & 1 & 1 & 23 & 0.04 & 0.04 & 0.05 & 0.09 & 0.07 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT37 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 37 & 1 & 1 & 22 & 0.05 & 0.04 & 0.05 & 0.09 & 0.07 & 0.02 & 0.01 & 0.02 & 0.01 & 0.00 & 0.00 \\
CCEDT38 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 38 & 1 & 1 & 23 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
CCEDT39 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 39 & 1 & 1 & 22 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 \\
CCEDT40 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 40 & 1 & 1 & 22 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 \\
CCEDT41 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 41 & 1 & 1 & 21 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 \\
CCEDT42 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 42 & 1 & 1 & 20 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
CCEDT43 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 43 & 1 & 1 & 19 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
CCEDT44 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 44 & 1 & 1 & 18 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
CCEDT45 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 45 & 1 & 1 & 18 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
CCEDT46 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 46 & 1 & 1 & 18 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
CCEDT47 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 47 & 1 & 1 & 16 & 0.05 & 0.04 & 0.04 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
CCEDT48 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 48 & 1 & 1 & 16 & 0.05 & 0.04 & 0.05 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
CCEDT49 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 49 & 1 & 1 & 16 & 0.05 & 0.04 & 0.05 & 0.09 & 0.07 & 0.03 & 0.01 & 0.01 & 0.02 & 0.00 & 0.01 \\
CCEDT50 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 50 & 1 & 1 & 16 & 0.05 & 0.04 & 0.06 & 0.09 & 0.07 & 0.04 & 0.01 & 0.02 & 0.02 & 0.00 & 0.01 \\
CCEDT51 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 51 & 1 & 1 & 15 & 0.05 & 0.04 & 0.06 & 0.09 & 0.07 & 0.04 & 0.01 & 0.02 & 0.03 & 0.00 & 0.01 \\
CCEDT52 & USED CHILD CARE WHILE IN ED/TRN PRGRM IN WEEK 52 & 1 & 1 & 15 & 0.05 & 0.04 & 0.06 & 0.09 & 0.07 & 0.03 & 0.01 & 0.02 & 0.03 & 0.00 & 0.01 \\
CCJC1 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 1 & 1 & 1 & 38 & 0.01 & 0.00 & 0.05 & 0.02 & 0.00 & 0.04 & 0.03 & 0.03 & 0.03 & 0.03 & 0.02 \\
CCJC2 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 2 & 1 & 1 & 39 & 0.01 & 0.00 & 0.04 & 0.07 & 0.00 & 0.07 & 0.05 & 0.04 & 0.06 & 0.05 & 0.05 \\
CCJC3 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 3 & 1 & 1 & 39 & 0.02 & 0.00 & 0.05 & 0.07 & 0.00 & 0.09 & 0.08 & 0.06 & 0.09 & 0.09 & 0.08 \\
CCJC4 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 4 & 1 & 1 & 40 & 0.03 & 0.00 & 0.08 & 0.07 & 0.00 & 0.12 & 0.10 & 0.08 & 0.13 & 0.10 & 0.12 \\
CCJC5 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 5 & 1 & 1 & 38 & 0.03 & 0.00 & 0.08 & 0.07 & 0.00 & 0.13 & 0.11 & 0.09 & 0.13 & 0.14 & 0.13 \\
CCJC6 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 6 & 1 & 1 & 38 & 0.03 & 0.00 & 0.07 & 0.07 & 0.00 & 0.13 & 0.11 & 0.11 & 0.15 & 0.14 & 0.14 \\
CCJC7 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 7 & 1 & 1 & 39 & 0.03 & 0.00 & 0.05 & 0.05 & 0.00 & 0.14 & 0.12 & 0.12 & 0.16 & 0.15 & 0.14 \\
CCJC8 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 8 & 1 & 1 & 39 & 0.03 & 0.00 & 0.05 & 0.02 & 0.00 & 0.14 & 0.12 & 0.12 & 0.16 & 0.16 & 0.15 \\
CCJC9 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 9 & 1 & 1 & 37 & 0.03 & 0.00 & 0.05 & 0.02 & 0.00 & 0.14 & 0.13 & 0.10 & 0.16 & 0.16 & 0.15 \\
CCJC10 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 10 & 1 & 1 & 36 & 0.03 & 0.00 & 0.06 & 0.02 & 0.00 & 0.13 & 0.13 & 0.10 & 0.16 & 0.15 & 0.15 \\
CCJC11 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 11 & 1 & 1 & 36 & 0.03 & 0.00 & 0.04 & 0.02 & 0.00 & 0.12 & 0.14 & 0.10 & 0.16 & 0.15 & 0.15 \\
CCJC12 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 12 & 1 & 1 & 36 & 0.03 & 0.00 & 0.04 & 0.02 & 0.00 & 0.12 & 0.14 & 0.09 & 0.15 & 0.15 & 0.15 \\
CCJC13 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 13 & 1 & 1 & 34 & 0.02 & 0.00 & 0.05 & 0.02 & 0.02 & 0.11 & 0.13 & 0.09 & 0.15 & 0.15 & 0.15 \\
CCJC14 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 14 & 1 & 1 & 35 & 0.02 & 0.00 & 0.04 & 0.02 & 0.02 & 0.11 & 0.13 & 0.09 & 0.15 & 0.15 & 0.15 \\
CCJC15 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 15 & 1 & 1 & 34 & 0.02 & 0.00 & 0.04 & 0.02 & 0.02 & 0.10 & 0.13 & 0.09 & 0.15 & 0.15 & 0.15 \\
CCJC16 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 16 & 1 & 1 & 31 & 0.02 & 0.00 & 0.04 & 0.05 & 0.02 & 0.10 & 0.14 & 0.09 & 0.14 & 0.15 & 0.16 \\
CCJC17 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 17 & 1 & 1 & 30 & 0.02 & 0.00 & 0.04 & 0.05 & 0.02 & 0.09 & 0.14 & 0.09 & 0.14 & 0.15 & 0.16 \\
CCJC18 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 18 & 1 & 1 & 28 & 0.02 & 0.00 & 0.04 & 0.05 & 0.02 & 0.09 & 0.13 & 0.09 & 0.14 & 0.15 & 0.16 \\
CCJC19 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 19 & 1 & 1 & 27 & 0.02 & 0.00 & 0.04 & 0.05 & 0.02 & 0.08 & 0.13 & 0.09 & 0.13 & 0.14 & 0.16 \\
CCJC20 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 20 & 1 & 1 & 25 & 0.02 & 0.00 & 0.04 & 0.05 & 0.02 & 0.08 & 0.13 & 0.09 & 0.13 & 0.14 & 0.15 \\
CCJC21 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 21 & 1 & 1 & 21 & 0.02 & 0.00 & 0.04 & 0.05 & 0.02 & 0.08 & 0.13 & 0.09 & 0.13 & 0.15 & 0.15 \\
CCJC22 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 22 & 1 & 1 & 21 & 0.02 & 0.00 & 0.04 & 0.05 & 0.02 & 0.08 & 0.13 & 0.08 & 0.13 & 0.15 & 0.15 \\
CCJC23 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 23 & 1 & 1 & 20 & 0.02 & 0.00 & 0.03 & 0.05 & 0.02 & 0.07 & 0.13 & 0.08 & 0.12 & 0.15 & 0.15 \\
CCJC24 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 24 & 1 & 1 & 20 & 0.02 & 0.00 & 0.03 & 0.05 & 0.02 & 0.07 & 0.13 & 0.08 & 0.12 & 0.15 & 0.15 \\
CCJC25 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 25 & 1 & 1 & 19 & 0.02 & 0.00 & 0.03 & 0.05 & 0.02 & 0.07 & 0.13 & 0.08 & 0.12 & 0.15 & 0.15 \\
CCJC26 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 26 & 1 & 1 & 19 & 0.02 & 0.00 & 0.03 & 0.05 & 0.02 & 0.06 & 0.13 & 0.08 & 0.12 & 0.15 & 0.15 \\
CCJC27 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 27 & 1 & 1 & 19 & 0.02 & 0.00 & 0.02 & 0.05 & 0.02 & 0.06 & 0.13 & 0.08 & 0.12 & 0.15 & 0.16 \\
CCJC28 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 28 & 1 & 1 & 19 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.05 & 0.13 & 0.07 & 0.11 & 0.14 & 0.15 \\
CCJC29 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 29 & 1 & 1 & 17 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.05 & 0.13 & 0.07 & 0.11 & 0.14 & 0.15 \\
CCJC30 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 30 & 1 & 1 & 16 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.05 & 0.13 & 0.06 & 0.11 & 0.13 & 0.16 \\
CCJC31 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 31 & 1 & 1 & 16 & 0.01 & 0.00 & 0.03 & 0.05 & 0.02 & 0.05 & 0.13 & 0.06 & 0.10 & 0.13 & 0.16 \\
CCJC32 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 32 & 1 & 1 & 16 & 0.01 & 0.00 & 0.03 & 0.05 & 0.02 & 0.04 & 0.13 & 0.06 & 0.10 & 0.13 & 0.16 \\
CCJC33 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 33 & 1 & 1 & 16 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.04 & 0.13 & 0.06 & 0.09 & 0.13 & 0.16 \\
CCJC34 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 34 & 1 & 1 & 14 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.04 & 0.13 & 0.06 & 0.09 & 0.13 & 0.16 \\
CCJC35 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 35 & 1 & 1 & 14 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.04 & 0.13 & 0.05 & 0.08 & 0.13 & 0.15 \\
CCJC36 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 36 & 1 & 1 & 14 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.03 & 0.13 & 0.05 & 0.08 & 0.13 & 0.16 \\
CCJC37 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 37 & 1 & 1 & 13 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.03 & 0.13 & 0.05 & 0.08 & 0.13 & 0.16 \\
CCJC38 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 38 & 1 & 1 & 13 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.03 & 0.12 & 0.05 & 0.07 & 0.13 & 0.16 \\
CCJC39 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 39 & 1 & 1 & 11 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.03 & 0.12 & 0.05 & 0.06 & 0.13 & 0.16 \\
CCJC40 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 40 & 1 & 1 & 9 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.03 & 0.12 & 0.05 & 0.06 & 0.13 & 0.16 \\
CCJC41 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 41 & 1 & 1 & 8 & 0.01 & 0.00 & 0.01 & 0.05 & 0.02 & 0.03 & 0.12 & 0.05 & 0.05 & 0.14 & 0.16 \\
CCJC42 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 42 & 1 & 1 & 7 & 0.01 & 0.00 & 0.01 & 0.05 & 0.02 & 0.02 & 0.12 & 0.05 & 0.04 & 0.14 & 0.16 \\
CCJC43 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 43 & 1 & 1 & 7 & 0.01 & 0.00 & 0.01 & 0.05 & 0.02 & 0.02 & 0.12 & 0.05 & 0.04 & 0.14 & 0.16 \\
CCJC44 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 44 & 1 & 1 & 6 & 0.01 & 0.00 & 0.01 & 0.05 & 0.02 & 0.02 & 0.12 & 0.05 & 0.04 & 0.13 & 0.16 \\
CCJC45 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 45 & 1 & 1 & 6 & 0.01 & 0.00 & 0.01 & 0.05 & 0.02 & 0.02 & 0.12 & 0.05 & 0.03 & 0.13 & 0.16 \\
CCJC46 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 46 & 1 & 1 & 6 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.01 & 0.12 & 0.05 & 0.03 & 0.13 & 0.16 \\
CCJC47 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 47 & 1 & 1 & 6 & 0.01 & 0.00 & 0.02 & 0.05 & 0.02 & 0.01 & 0.12 & 0.05 & 0.03 & 0.13 & 0.16 \\
CCJC48 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 48 & 1 & 1 & 5 & 0.01 & 0.00 & 0.01 & 0.05 & 0.02 & 0.01 & 0.12 & 0.05 & 0.02 & 0.13 & 0.16 \\
CCJC49 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 49 & 1 & 1 & 4 & 0.01 & 0.00 & 0.01 & 0.05 & 0.02 & 0.01 & 0.12 & 0.05 & 0.02 & 0.13 & 0.16 \\
CCJC50 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 50 & 1 & 1 & 3 & 0.01 & 0.00 & 0.01 & 0.05 & 0.02 & 0.01 & 0.12 & 0.05 & 0.02 & 0.13 & 0.16 \\
CCJC51 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 51 & 1 & 1 & 3 & 0.00 & 0.00 & 0.01 & 0.05 & 0.02 & 0.01 & 0.12 & 0.05 & 0.02 & 0.13 & 0.16 \\
CCJC52 & USED CHILD CARE WHILE IN JOB CORPS IN WEEK 52 & 1 & 1 & 4 & 0.00 & 0.00 & 0.01 & 0.05 & 0.05 & 0.00 & 0.12 & 0.05 & 0.01 & 0.11 & 0.16 \\
UIH1 & GOT UI BENEFITS IN WEEK 1 & 1 & 1 & 262 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH2 & GOT UI BENEFITS IN WEEK 2 & 1 & 1 & 262 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH3 & GOT UI BENEFITS IN WEEK 3 & 1 & 1 & 262 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH4 & GOT UI BENEFITS IN WEEK 4 & 1 & 1 & 262 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH5 & GOT UI BENEFITS IN WEEK 5 & 1 & 1 & 262 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH6 & GOT UI BENEFITS IN WEEK 6 & 1 & 1 & 262 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH7 & GOT UI BENEFITS IN WEEK 7 & 1 & 1 & 262 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH8 & GOT UI BENEFITS IN WEEK 8 & 1 & 1 & 262 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH9 & GOT UI BENEFITS IN WEEK 9 & 1 & 1 & 262 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH10 & GOT UI BENEFITS IN WEEK 10 & 1 & 1 & 263 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH11 & GOT UI BENEFITS IN WEEK 11 & 1 & 1 & 263 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH12 & GOT UI BENEFITS IN WEEK 12 & 1 & 1 & 263 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH13 & GOT UI BENEFITS IN WEEK 13 & 1 & 1 & 22 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH14 & GOT UI BENEFITS IN WEEK 14 & 1 & 1 & 22 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH15 & GOT UI BENEFITS IN WEEK 15 & 1 & 1 & 22 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH16 & GOT UI BENEFITS IN WEEK 16 & 1 & 1 & 22 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH17 & GOT UI BENEFITS IN WEEK 17 & 1 & 1 & 22 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH18 & GOT UI BENEFITS IN WEEK 18 & 1 & 1 & 22 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH19 & GOT UI BENEFITS IN WEEK 19 & 1 & 1 & 23 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH20 & GOT UI BENEFITS IN WEEK 20 & 1 & 1 & 23 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH21 & GOT UI BENEFITS IN WEEK 21 & 1 & 1 & 23 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH22 & GOT UI BENEFITS IN WEEK 22 & 1 & 1 & 23 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH23 & GOT UI BENEFITS IN WEEK 23 & 1 & 1 & 23 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH24 & GOT UI BENEFITS IN WEEK 24 & 1 & 1 & 23 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH25 & GOT UI BENEFITS IN WEEK 25 & 1 & 1 & 23 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH26 & GOT UI BENEFITS IN WEEK 26 & 1 & 1 & 23 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH27 & GOT UI BENEFITS IN WEEK 27 & 1 & 1 & 23 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH28 & GOT UI BENEFITS IN WEEK 28 & 1 & 1 & 23 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH29 & GOT UI BENEFITS IN WEEK 29 & 1 & 1 & 23 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH30 & GOT UI BENEFITS IN WEEK 30 & 1 & 1 & 23 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH31 & GOT UI BENEFITS IN WEEK 31 & 1 & 1 & 24 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH32 & GOT UI BENEFITS IN WEEK 32 & 1 & 1 & 23 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH33 & GOT UI BENEFITS IN WEEK 33 & 1 & 1 & 23 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH34 & GOT UI BENEFITS IN WEEK 34 & 1 & 1 & 23 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH35 & GOT UI BENEFITS IN WEEK 35 & 1 & 1 & 23 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH36 & GOT UI BENEFITS IN WEEK 36 & 1 & 1 & 23 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH37 & GOT UI BENEFITS IN WEEK 37 & 1 & 1 & 21 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH38 & GOT UI BENEFITS IN WEEK 38 & 1 & 1 & 21 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH39 & GOT UI BENEFITS IN WEEK 39 & 1 & 1 & 21 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH40 & GOT UI BENEFITS IN WEEK 40 & 1 & 1 & 21 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH41 & GOT UI BENEFITS IN WEEK 41 & 1 & 1 & 21 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH42 & GOT UI BENEFITS IN WEEK 42 & 1 & 1 & 21 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH43 & GOT UI BENEFITS IN WEEK 43 & 1 & 1 & 21 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH44 & GOT UI BENEFITS IN WEEK 44 & 1 & 1 & 21 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH45 & GOT UI BENEFITS IN WEEK 45 & 1 & 1 & 21 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH46 & GOT UI BENEFITS IN WEEK 46 & 1 & 1 & 20 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH47 & GOT UI BENEFITS IN WEEK 47 & 1 & 1 & 20 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH48 & GOT UI BENEFITS IN WEEK 48 & 1 & 1 & 20 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH49 & GOT UI BENEFITS IN WEEK 49 & 1 & 1 & 19 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH50 & GOT UI BENEFITS IN WEEK 50 & 1 & 1 & 19 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH51 & GOT UI BENEFITS IN WEEK 51 & 1 & 1 & 19 & 0.00 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
UIH52 & GOT UI BENEFITS IN WEEK 52 & 1 & 1 & 18 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
HWH1 & HOURS WORKED IN WEEK 1 & 3 & 1 & 552 & 9.14 & 8.11 & 9.24 & 5.71 & 9.43 & 6.79 & 6.90 & 6.36 & 7.76 & 7.70 & 7.31 \\
HWH2 & HOURS WORKED IN WEEK 2 & 3 & 1 & 622 & 9.45 & 8.64 & 8.67 & 4.29 & 9.43 & 5.72 & 5.24 & 5.94 & 6.99 & 5.47 & 6.07 \\
HWH3 & HOURS WORKED IN WEEK 3 & 3 & 1 & 618 & 9.85 & 9.46 & 8.58 & 3.67 & 9.57 & 5.19 & 4.83 & 5.24 & 5.98 & 4.10 & 5.14 \\
HWH4 & HOURS WORKED IN WEEK 4 & 3 & 1 & 626 & 10.03 & 10.05 & 9.23 & 4.24 & 9.88 & 5.07 & 4.25 & 3.75 & 4.88 & 1.78 & 4.02 \\
HWH5 & HOURS WORKED IN WEEK 5 & 3 & 1 & 629 & 10.17 & 10.73 & 9.35 & 4.24 & 9.88 & 4.70 & 3.84 & 3.76 & 4.34 & 2.33 & 3.53 \\
HWH6 & HOURS WORKED IN WEEK 6 & 3 & 1 & 632 & 10.56 & 11.29 & 9.80 & 5.19 & 12.12 & 4.71 & 3.46 & 4.08 & 3.74 & 1.95 & 2.66 \\
HWH7 & HOURS WORKED IN WEEK 7 & 3 & 1 & 635 & 10.96 & 11.62 & 10.77 & 4.71 & 13.31 & 4.88 & 3.49 & 3.44 & 3.73 & 2.44 & 2.35 \\
HWH8 & HOURS WORKED IN WEEK 8 & 3 & 1 & 639 & 11.33 & 12.27 & 11.31 & 4.71 & 12.48 & 5.20 & 3.25 & 3.38 & 3.86 & 2.44 & 2.68 \\
HWH9 & HOURS WORKED IN WEEK 9 & 3 & 1 & 644 & 11.60 & 12.60 & 11.51 & 4.71 & 12.48 & 5.25 & 3.03 & 3.27 & 3.92 & 2.11 & 2.62 \\
HWH10 & HOURS WORKED IN WEEK 10 & 3 & 1 & 644 & 11.97 & 12.82 & 11.89 & 5.31 & 12.48 & 5.67 & 2.88 & 3.49 & 4.10 & 2.05 & 2.58 \\
HWH11 & HOURS WORKED IN WEEK 11 & 3 & 1 & 645 & 11.98 & 13.23 & 12.19 & 5.31 & 14.43 & 5.86 & 3.15 & 3.14 & 4.30 & 2.05 & 2.72 \\
HWH12 & HOURS WORKED IN WEEK 12 & 3 & 1 & 652 & 12.40 & 13.46 & 12.55 & 4.02 & 14.43 & 6.39 & 2.84 & 3.16 & 4.56 & 2.58 & 2.66 \\
HWH13 & HOURS WORKED IN WEEK 13 & 3 & 1 & 650 & 12.53 & 13.78 & 13.49 & 3.26 & 14.19 & 6.75 & 3.02 & 3.16 & 4.91 & 3.00 & 2.46 \\
HWH14 & HOURS WORKED IN WEEK 14 & 3 & 1 & 657 & 12.81 & 13.89 & 13.45 & 3.26 & 13.62 & 6.93 & 2.94 & 3.29 & 4.88 & 3.48 & 2.36 \\
HWH15 & HOURS WORKED IN WEEK 15 & 3 & 1 & 654 & 12.94 & 14.14 & 13.58 & 4.40 & 13.05 & 7.39 & 3.41 & 3.30 & 5.05 & 3.48 & 2.54 \\
HWH16 & HOURS WORKED IN WEEK 16 & 3 & 1 & 656 & 13.05 & 14.24 & 13.46 & 4.40 & 13.05 & 7.70 & 3.55 & 2.93 & 5.29 & 4.25 & 2.49 \\
HWH17 & HOURS WORKED IN WEEK 17 & 3 & 1 & 660 & 13.41 & 14.47 & 14.20 & 3.45 & 12.86 & 8.10 & 3.57 & 3.24 & 5.61 & 3.87 & 2.53 \\
HWH18 & HOURS WORKED IN WEEK 18 & 3 & 1 & 657 & 13.65 & 14.51 & 13.86 & 4.74 & 13.21 & 8.57 & 3.87 & 3.49 & 6.19 & 3.87 & 2.57 \\
HWH19 & HOURS WORKED IN WEEK 19 & 3 & 1 & 656 & 13.89 & 14.81 & 14.72 & 5.74 & 13.21 & 9.01 & 4.19 & 3.49 & 6.54 & 3.87 & 2.61 \\
HWH20 & HOURS WORKED IN WEEK 20 & 3 & 1 & 653 & 13.91 & 15.31 & 14.38 & 4.60 & 14.29 & 9.51 & 4.36 & 3.33 & 7.08 & 3.60 & 2.96 \\
HWH21 & HOURS WORKED IN WEEK 21 & 3 & 1 & 654 & 14.18 & 15.31 & 14.88 & 4.60 & 13.81 & 9.66 & 4.13 & 3.33 & 7.81 & 4.38 & 2.99 \\
HWH22 & HOURS WORKED IN WEEK 22 & 3 & 1 & 652 & 14.29 & 15.36 & 14.84 & 4.60 & 14.64 & 10.11 & 4.50 & 3.59 & 8.02 & 4.86 & 2.98 \\
HWH23 & HOURS WORKED IN WEEK 23 & 3 & 1 & 652 & 14.61 & 15.45 & 15.91 & 3.60 & 13.33 & 10.23 & 4.62 & 3.73 & 8.28 & 5.31 & 3.22 \\
HWH24 & HOURS WORKED IN WEEK 24 & 3 & 1 & 645 & 14.89 & 15.64 & 15.34 & 4.17 & 13.48 & 10.67 & 4.89 & 3.82 & 8.48 & 5.31 & 3.50 \\
HWH25 & HOURS WORKED IN WEEK 25 & 3 & 1 & 643 & 15.09 & 15.98 & 15.58 & 6.79 & 14.31 & 11.02 & 5.24 & 3.58 & 8.89 & 4.97 & 3.46 \\
HWH26 & HOURS WORKED IN WEEK 26 & 3 & 1 & 640 & 15.52 & 16.14 & 15.50 & 6.79 & 13.36 & 11.42 & 5.00 & 3.58 & 9.57 & 4.97 & 3.63 \\
HWH27 & HOURS WORKED IN WEEK 27 & 3 & 1 & 635 & 15.69 & 16.41 & 15.44 & 7.21 & 12.79 & 11.66 & 4.91 & 3.76 & 9.70 & 4.67 & 3.97 \\
HWH28 & HOURS WORKED IN WEEK 28 & 3 & 1 & 637 & 15.87 & 16.32 & 16.17 & 8.69 & 13.36 & 12.10 & 5.01 & 3.62 & 10.00 & 4.67 & 4.04 \\
HWH29 & HOURS WORKED IN WEEK 29 & 3 & 1 & 633 & 16.21 & 16.45 & 16.52 & 8.69 & 13.36 & 12.00 & 5.16 & 3.82 & 10.76 & 4.19 & 3.98 \\
HWH30 & HOURS WORKED IN WEEK 30 & 3 & 1 & 633 & 16.39 & 16.43 & 16.60 & 8.74 & 15.38 & 12.67 & 5.57 & 4.31 & 10.94 & 4.54 & 3.93 \\
HWH31 & HOURS WORKED IN WEEK 31 & 3 & 1 & 630 & 16.43 & 16.77 & 16.75 & 9.81 & 16.10 & 12.84 & 5.88 & 4.64 & 11.08 & 5.28 & 3.99 \\
HWH32 & HOURS WORKED IN WEEK 32 & 3 & 1 & 630 & 16.41 & 16.78 & 16.53 & 9.24 & 16.48 & 12.95 & 5.63 & 5.61 & 11.50 & 6.14 & 4.09 \\
HWH33 & HOURS WORKED IN WEEK 33 & 3 & 1 & 628 & 16.63 & 17.08 & 16.64 & 10.93 & 15.64 & 13.18 & 6.03 & 5.05 & 12.17 & 6.62 & 4.11 \\
HWH34 & HOURS WORKED IN WEEK 34 & 3 & 1 & 623 & 16.70 & 17.22 & 16.37 & 11.64 & 16.60 & 13.08 & 6.01 & 4.86 & 12.52 & 6.53 & 4.30 \\
HWH35 & HOURS WORKED IN WEEK 35 & 3 & 1 & 620 & 16.51 & 17.57 & 17.60 & 12.57 & 15.07 & 13.06 & 5.93 & 5.65 & 13.16 & 7.80 & 4.14 \\
HWH36 & HOURS WORKED IN WEEK 36 & 3 & 1 & 612 & 16.86 & 17.64 & 18.22 & 11.81 & 14.00 & 13.11 & 5.66 & 5.66 & 14.12 & 7.33 & 4.31 \\
HWH37 & HOURS WORKED IN WEEK 37 & 3 & 1 & 607 & 16.99 & 17.97 & 17.88 & 9.68 & 14.24 & 13.57 & 5.34 & 5.61 & 14.73 & 7.80 & 4.63 \\
HWH38 & HOURS WORKED IN WEEK 38 & 3 & 1 & 600 & 17.07 & 17.96 & 18.10 & 9.68 & 14.95 & 13.53 & 5.51 & 5.97 & 15.04 & 6.79 & 4.77 \\
HWH39 & HOURS WORKED IN WEEK 39 & 3 & 1 & 595 & 17.29 & 18.03 & 17.69 & 10.66 & 13.71 & 13.56 & 5.60 & 6.08 & 15.25 & 7.13 & 4.61 \\
HWH40 & HOURS WORKED IN WEEK 40 & 3 & 1 & 586 & 17.79 & 17.98 & 18.30 & 9.55 & 13.32 & 13.99 & 5.87 & 5.97 & 15.62 & 6.75 & 4.57 \\
HWH41 & HOURS WORKED IN WEEK 41 & 3 & 1 & 579 & 17.72 & 17.93 & 17.60 & 9.12 & 11.49 & 14.20 & 5.76 & 5.58 & 15.97 & 6.65 & 4.90 \\
HWH42 & HOURS WORKED IN WEEK 42 & 3 & 1 & 572 & 17.87 & 18.12 & 17.51 & 8.05 & 9.90 & 14.63 & 5.61 & 5.19 & 16.31 & 5.67 & 5.09 \\
HWH43 & HOURS WORKED IN WEEK 43 & 3 & 1 & 565 & 18.07 & 18.20 & 17.60 & 8.52 & 12.02 & 14.89 & 6.21 & 5.14 & 17.26 & 5.73 & 4.97 \\
HWH44 & HOURS WORKED IN WEEK 44 & 3 & 1 & 564 & 18.02 & 18.38 & 17.98 & 9.24 & 12.02 & 15.30 & 6.13 & 5.06 & 18.19 & 5.73 & 4.94 \\
HWH45 & HOURS WORKED IN WEEK 45 & 3 & 1 & 559 & 17.95 & 18.52 & 17.70 & 8.88 & 11.54 & 15.70 & 6.69 & 4.45 & 18.88 & 5.78 & 5.20 \\
HWH46 & HOURS WORKED IN WEEK 46 & 3 & 1 & 554 & 17.81 & 18.61 & 17.45 & 10.02 & 10.54 & 15.90 & 6.52 & 4.53 & 19.52 & 6.50 & 4.92 \\
HWH47 & HOURS WORKED IN WEEK 47 & 3 & 1 & 541 & 17.84 & 18.41 & 17.93 & 10.02 & 10.54 & 15.89 & 6.95 & 5.10 & 19.54 & 5.58 & 5.22 \\
HWH48 & HOURS WORKED IN WEEK 48 & 3 & 1 & 534 & 18.02 & 18.31 & 17.93 & 8.69 & 8.71 & 16.14 & 7.34 & 5.30 & 19.65 & 6.10 & 5.29 \\
HWH49 & HOURS WORKED IN WEEK 49 & 3 & 1 & 521 & 17.91 & 18.32 & 17.58 & 9.05 & 8.71 & 16.05 & 7.14 & 4.89 & 19.88 & 6.94 & 5.57 \\
HWH50 & HOURS WORKED IN WEEK 50 & 3 & 1 & 510 & 18.32 & 18.03 & 17.88 & 7.62 & 7.85 & 15.92 & 6.92 & 4.86 & 20.41 & 6.94 & 5.80 \\
HWH51 & HOURS WORKED IN WEEK 51 & 3 & 1 & 505 & 18.09 & 18.15 & 17.61 & 8.17 & 8.83 & 15.99 & 6.92 & 4.52 & 20.11 & 8.11 & 5.84 \\
HWH52 & HOURS WORKED IN WEEK 52 & 3 & 1 & 500 & 17.90 & 18.30 & 17.20 & 7.50 & 6.68 & 15.87 & 6.96 & 4.79 & 20.72 & 8.44 & 5.87 \\
EARNH1 & EARNINGS IN WEEK 1 & 3 & 1 & 552 & 49.55 & 42.83 & 50.70 & 32.57 & 44.96 & 35.81 & 37.59 & 27.29 & 40.14 & 35.58 & 36.39 \\
EARNH2 & EARNINGS IN WEEK 2 & 3 & 1 & 622 & 51.94 & 47.64 & 49.61 & 23.10 & 45.44 & 30.45 & 26.97 & 25.64 & 39.49 & 26.01 & 30.04 \\
EARNH3 & EARNINGS IN WEEK 3 & 3 & 1 & 618 & 55.49 & 51.45 & 52.29 & 18.80 & 51.52 & 28.24 & 25.49 & 22.06 & 34.68 & 19.78 & 25.69 \\
EARNH4 & EARNINGS IN WEEK 4 & 3 & 1 & 626 & 57.43 & 55.44 & 59.25 & 21.23 & 53.36 & 27.33 & 22.99 & 17.33 & 28.49 & 8.42 & 20.42 \\
EARNH5 & EARNINGS IN WEEK 5 & 3 & 1 & 629 & 58.66 & 59.54 & 58.77 & 21.23 & 53.36 & 25.63 & 19.90 & 18.44 & 26.77 & 10.80 & 17.82 \\
EARNH6 & EARNINGS IN WEEK 6 & 3 & 1 & 632 & 61.03 & 62.56 & 61.02 & 26.38 & 63.90 & 25.53 & 17.35 & 20.70 & 22.67 & 8.67 & 12.83 \\
EARNH7 & EARNINGS IN WEEK 7 & 3 & 1 & 635 & 63.67 & 64.39 & 65.99 & 26.38 & 70.45 & 26.25 & 17.63 & 15.74 & 22.78 & 11.19 & 11.10 \\
EARNH8 & EARNINGS IN WEEK 8 & 3 & 1 & 639 & 65.54 & 68.08 & 67.08 & 26.38 & 66.79 & 27.76 & 17.59 & 16.12 & 23.03 & 11.19 & 14.00 \\
EARNH9 & EARNINGS IN WEEK 9 & 3 & 1 & 644 & 67.25 & 69.82 & 68.14 & 26.38 & 66.79 & 27.81 & 17.07 & 15.65 & 22.70 & 9.75 & 13.58 \\
EARNH10 & EARNINGS IN WEEK 10 & 3 & 1 & 644 & 69.79 & 71.53 & 71.11 & 29.36 & 66.79 & 30.05 & 16.41 & 16.76 & 23.71 & 9.74 & 13.15 \\
EARNH11 & EARNINGS IN WEEK 11 & 3 & 1 & 645 & 69.81 & 74.19 & 72.85 & 29.36 & 80.17 & 31.45 & 17.98 & 14.80 & 24.86 & 9.74 & 14.49 \\
EARNH12 & EARNINGS IN WEEK 12 & 3 & 1 & 652 & 72.73 & 75.87 & 74.96 & 20.94 & 80.17 & 34.53 & 16.39 & 14.88 & 26.32 & 12.38 & 14.24 \\
EARNH13 & EARNINGS IN WEEK 13 & 3 & 1 & 650 & 74.02 & 77.71 & 81.07 & 17.13 & 78.77 & 35.69 & 17.21 & 14.88 & 27.56 & 14.18 & 13.44 \\
EARNH14 & EARNINGS IN WEEK 14 & 3 & 1 & 657 & 75.49 & 78.60 & 80.82 & 17.13 & 76.34 & 36.88 & 16.94 & 15.47 & 27.54 & 16.26 & 12.80 \\
EARNH15 & EARNINGS IN WEEK 15 & 3 & 1 & 654 & 76.26 & 80.24 & 81.33 & 23.13 & 73.05 & 39.52 & 19.11 & 15.27 & 28.20 & 16.26 & 14.37 \\
EARNH16 & EARNINGS IN WEEK 16 & 3 & 1 & 656 & 77.08 & 81.23 & 80.50 & 23.13 & 73.05 & 41.45 & 20.40 & 12.71 & 30.49 & 21.14 & 14.13 \\
EARNH17 & EARNINGS IN WEEK 17 & 3 & 1 & 660 & 80.36 & 83.06 & 84.25 & 17.98 & 71.91 & 44.12 & 20.54 & 15.06 & 32.37 & 19.14 & 14.09 \\
EARNH18 & EARNINGS IN WEEK 18 & 3 & 1 & 657 & 82.17 & 83.35 & 82.39 & 21.26 & 73.43 & 46.75 & 22.45 & 16.25 & 36.44 & 19.14 & 14.27 \\
EARNH19 & EARNINGS IN WEEK 19 & 3 & 1 & 656 & 83.43 & 85.05 & 87.04 & 26.26 & 73.43 & 49.14 & 23.93 & 16.25 & 38.95 & 19.14 & 14.24 \\
EARNH20 & EARNINGS IN WEEK 20 & 3 & 1 & 653 & 83.51 & 87.79 & 85.38 & 20.26 & 78.52 & 52.67 & 24.69 & 17.36 & 42.15 & 18.00 & 18.15 \\
EARNH21 & EARNINGS IN WEEK 21 & 3 & 1 & 654 & 85.27 & 88.21 & 86.62 & 20.26 & 76.85 & 53.43 & 23.29 & 17.36 & 46.81 & 21.52 & 18.40 \\
EARNH22 & EARNINGS IN WEEK 22 & 3 & 1 & 652 & 85.83 & 88.89 & 86.98 & 20.26 & 82.24 & 56.76 & 25.56 & 18.52 & 48.46 & 23.11 & 18.35 \\
EARNH23 & EARNINGS IN WEEK 23 & 3 & 1 & 652 & 87.61 & 89.14 & 91.98 & 15.26 & 75.96 & 58.28 & 26.18 & 19.14 & 49.79 & 25.88 & 19.19 \\
EARNH24 & EARNINGS IN WEEK 24 & 3 & 1 & 645 & 90.02 & 89.82 & 88.97 & 17.69 & 74.48 & 60.42 & 27.58 & 19.83 & 51.18 & 25.88 & 20.69 \\
EARNH25 & EARNINGS IN WEEK 25 & 3 & 1 & 643 & 91.03 & 91.73 & 90.04 & 31.23 & 80.73 & 62.21 & 29.29 & 18.84 & 53.43 & 24.14 & 20.79 \\
EARNH26 & EARNINGS IN WEEK 26 & 3 & 1 & 640 & 93.79 & 92.70 & 89.08 & 31.23 & 76.68 & 64.91 & 27.84 & 18.84 & 57.79 & 24.14 & 22.01 \\
EARNH27 & EARNINGS IN WEEK 27 & 3 & 1 & 635 & 95.12 & 94.56 & 89.59 & 33.37 & 73.97 & 66.39 & 27.23 & 19.59 & 58.76 & 22.30 & 24.05 \\
EARNH28 & EARNINGS IN WEEK 28 & 3 & 1 & 637 & 96.28 & 93.91 & 93.08 & 40.09 & 76.68 & 68.61 & 27.56 & 18.88 & 60.35 & 22.30 & 24.32 \\
EARNH29 & EARNINGS IN WEEK 29 & 3 & 1 & 633 & 98.38 & 94.67 & 94.58 & 42.78 & 76.68 & 68.89 & 28.92 & 20.78 & 64.85 & 20.11 & 23.62 \\
EARNH30 & EARNINGS IN WEEK 30 & 3 & 1 & 633 & 100.06 & 95.04 & 95.75 & 41.22 & 87.92 & 72.99 & 31.31 & 23.25 & 66.45 & 21.24 & 22.76 \\
EARNH31 & EARNINGS IN WEEK 31 & 3 & 1 & 630 & 100.44 & 96.94 & 97.02 & 47.38 & 91.50 & 73.69 & 33.01 & 23.93 & 67.32 & 25.40 & 23.22 \\
EARNH32 & EARNINGS IN WEEK 32 & 3 & 1 & 630 & 100.42 & 97.38 & 97.16 & 44.95 & 93.11 & 74.10 & 32.01 & 29.71 & 70.06 & 29.93 & 23.24 \\
EARNH33 & EARNINGS IN WEEK 33 & 3 & 1 & 628 & 101.51 & 98.81 & 97.80 & 52.13 & 86.86 & 75.84 & 33.70 & 26.96 & 74.11 & 32.10 & 23.38 \\
EARNH34 & EARNINGS IN WEEK 34 & 3 & 1 & 623 & 102.05 & 99.85 & 96.58 & 55.24 & 91.63 & 74.84 & 33.63 & 25.73 & 76.20 & 32.43 & 23.44 \\
EARNH35 & EARNINGS IN WEEK 35 & 3 & 1 & 620 & 100.82 & 101.79 & 103.32 & 62.58 & 83.29 & 74.85 & 32.79 & 29.42 & 80.20 & 39.99 & 21.67 \\
EARNH36 & EARNINGS IN WEEK 36 & 3 & 1 & 612 & 103.45 & 102.46 & 107.19 & 59.34 & 78.20 & 75.28 & 31.59 & 30.15 & 85.25 & 37.68 & 22.83 \\
EARNH37 & EARNINGS IN WEEK 37 & 3 & 1 & 607 & 104.48 & 104.24 & 104.63 & 49.58 & 75.85 & 78.14 & 29.61 & 30.64 & 89.33 & 39.64 & 24.59 \\
EARNH38 & EARNINGS IN WEEK 38 & 3 & 1 & 600 & 104.99 & 104.25 & 105.71 & 49.58 & 80.31 & 78.20 & 30.31 & 31.44 & 91.95 & 35.53 & 26.14 \\
EARNH39 & EARNINGS IN WEEK 39 & 3 & 1 & 595 & 106.40 & 104.59 & 103.74 & 57.39 & 74.62 & 77.53 & 30.93 & 32.19 & 93.32 & 35.96 & 25.45 \\
EARNH40 & EARNINGS IN WEEK 40 & 3 & 1 & 586 & 108.42 & 104.37 & 104.34 & 51.86 & 72.96 & 79.88 & 32.41 & 32.08 & 95.45 & 34.04 & 26.10 \\
EARNH41 & EARNINGS IN WEEK 41 & 3 & 1 & 579 & 108.23 & 104.40 & 100.55 & 50.04 & 61.49 & 81.39 & 30.98 & 30.18 & 97.04 & 33.80 & 27.81 \\
EARNH42 & EARNINGS IN WEEK 42 & 3 & 1 & 572 & 109.15 & 105.37 & 100.14 & 45.79 & 50.48 & 84.46 & 29.85 & 27.67 & 100.19 & 29.93 & 28.63 \\
EARNH43 & EARNINGS IN WEEK 43 & 3 & 1 & 565 & 110.77 & 105.90 & 101.98 & 47.93 & 60.87 & 86.59 & 33.18 & 28.89 & 105.98 & 30.68 & 27.40 \\
EARNH44 & EARNINGS IN WEEK 44 & 3 & 1 & 564 & 111.29 & 107.04 & 104.00 & 51.86 & 60.87 & 88.79 & 32.90 & 27.65 & 111.29 & 30.68 & 27.08 \\
EARNH45 & EARNINGS IN WEEK 45 & 3 & 1 & 559 & 110.56 & 107.84 & 102.74 & 49.90 & 59.16 & 91.27 & 35.51 & 25.58 & 115.92 & 30.92 & 29.20 \\
EARNH46 & EARNINGS IN WEEK 46 & 3 & 1 & 554 & 108.94 & 108.39 & 103.87 & 56.42 & 58.31 & 92.08 & 35.16 & 26.76 & 119.23 & 33.99 & 27.65 \\
EARNH47 & EARNINGS IN WEEK 47 & 3 & 1 & 541 & 108.91 & 107.32 & 106.76 & 56.42 & 58.31 & 93.13 & 37.25 & 29.43 & 120.19 & 30.55 & 29.28 \\
EARNH48 & EARNINGS IN WEEK 48 & 3 & 1 & 534 & 110.10 & 107.53 & 108.27 & 46.26 & 46.12 & 93.77 & 39.33 & 30.24 & 120.71 & 32.38 & 29.21 \\
EARNH49 & EARNINGS IN WEEK 49 & 3 & 1 & 521 & 109.33 & 108.15 & 106.05 & 48.22 & 46.12 & 93.20 & 38.05 & 27.91 & 120.85 & 39.26 & 30.93 \\
EARNH50 & EARNINGS IN WEEK 50 & 3 & 1 & 510 & 111.78 & 106.34 & 108.30 & 41.32 & 42.06 & 92.94 & 37.55 & 27.76 & 125.28 & 40.00 & 32.37 \\
EARNH51 & EARNINGS IN WEEK 51 & 3 & 1 & 505 & 111.02 & 106.91 & 106.38 & 44.70 & 43.28 & 93.14 & 37.61 & 25.98 & 123.97 & 45.32 & 32.91 \\
EARNH52 & EARNINGS IN WEEK 52 & 3 & 1 & 500 & 110.08 & 108.13 & 104.36 & 41.36 & 32.60 & 92.72 & 37.98 & 27.29 & 127.87 & 47.98 & 32.48 \\
EDTA1 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 1 & 3 & 1 & 6074 & 4.15 & 5.22 & 6.03 & 2.96 & 10.29 & 4.88 & 4.41 & 7.03 & 3.12 & 5.80 & 3.91 \\
EDTA2 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 2 & 3 & 1 & 6080 & 2.83 & 3.92 & 3.91 & 2.96 & 8.71 & 2.80 & 3.23 & 4.62 & 2.11 & 3.00 & 1.96 \\
EDTA3 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 3 & 3 & 1 & 6086 & 2.64 & 3.84 & 3.45 & 2.96 & 8.71 & 2.33 & 2.38 & 3.70 & 1.71 & 3.00 & 1.30 \\
EDTA4 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 4 & 3 & 1 & 6085 & 2.43 & 3.90 & 3.41 & 4.44 & 8.71 & 2.04 & 1.91 & 2.92 & 1.18 & 2.33 & 0.99 \\
EDTA5 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 5 & 3 & 1 & 6083 & 2.48 & 4.06 & 3.52 & 4.07 & 7.06 & 1.57 & 1.88 & 2.07 & 0.73 & 1.56 & 0.81 \\
EDTA6 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 6 & 3 & 1 & 6084 & 2.54 & 4.22 & 3.38 & 4.44 & 7.06 & 1.59 & 1.77 & 1.86 & 0.66 & 0.67 & 0.54 \\
EDTA7 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 7 & 3 & 1 & 6086 & 2.63 & 4.38 & 3.15 & 5.37 & 9.41 & 1.69 & 1.77 & 1.86 & 0.64 & 0.67 & 0.36 \\
EDTA8 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 8 & 3 & 1 & 6090 & 2.59 & 4.41 & 3.10 & 6.30 & 11.76 & 1.57 & 1.77 & 1.36 & 0.64 & 0.67 & 0.36 \\
EDTA9 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 9 & 3 & 1 & 6088 & 2.58 & 4.44 & 2.58 & 6.30 & 11.76 & 1.62 & 1.70 & 0.81 & 0.64 & 0.67 & 0.36 \\
EDTA10 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 10 & 3 & 1 & 6091 & 2.43 & 4.55 & 2.69 & 7.04 & 11.76 & 1.63 & 1.73 & 0.81 & 0.57 & 0.67 & 0.36 \\
EDTA11 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 11 & 3 & 1 & 6094 & 2.42 & 4.62 & 3.05 & 7.04 & 11.76 & 1.63 & 1.70 & 0.81 & 0.46 & 0.67 & 0.36 \\
EDTA12 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 12 & 3 & 1 & 6096 & 2.41 & 4.74 & 3.19 & 5.56 & 11.76 & 1.74 & 1.67 & 0.81 & 0.41 & 0.67 & 0.36 \\
EDTA13 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 13 & 3 & 1 & 6095 & 2.44 & 4.81 & 3.60 & 5.56 & 11.76 & 1.71 & 1.89 & 0.81 & 0.41 & 0.67 & 0.23 \\
EDTA14 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 14 & 3 & 1 & 6092 & 2.40 & 4.92 & 3.78 & 5.56 & 11.76 & 1.81 & 1.43 & 0.81 & 0.51 & 0.67 & 0.27 \\
EDTA15 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 15 & 3 & 1 & 6092 & 2.41 & 5.01 & 3.78 & 5.56 & 11.76 & 1.84 & 1.43 & 1.03 & 0.59 & 1.56 & 0.26 \\
EDTA16 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 16 & 3 & 1 & 6090 & 2.44 & 4.98 & 3.42 & 5.56 & 11.76 & 1.97 & 1.52 & 1.03 & 0.64 & 1.56 & 0.26 \\
EDTA17 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 17 & 3 & 1 & 6088 & 2.43 & 4.97 & 3.57 & 6.00 & 11.76 & 1.97 & 1.27 & 1.03 & 0.81 & 1.56 & 0.42 \\
EDTA18 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 18 & 3 & 1 & 6086 & 2.29 & 5.10 & 3.39 & 6.74 & 15.06 & 1.86 & 1.22 & 1.03 & 0.75 & 1.56 & 0.35 \\
EDTA19 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 19 & 3 & 1 & 6086 & 2.34 & 5.06 & 3.92 & 6.74 & 15.06 & 1.95 & 1.22 & 1.45 & 0.81 & 1.56 & 0.35 \\
EDTA20 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 20 & 3 & 1 & 6083 & 2.38 & 5.02 & 3.92 & 6.74 & 15.06 & 1.98 & 1.30 & 1.45 & 0.81 & 1.89 & 0.35 \\
EDTA21 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 21 & 3 & 1 & 6082 & 2.40 & 5.12 & 3.85 & 6.74 & 15.06 & 2.02 & 1.43 & 1.45 & 0.81 & 1.36 & 0.35 \\
EDTA22 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 22 & 3 & 1 & 6082 & 2.45 & 5.12 & 3.29 & 6.74 & 15.06 & 2.03 & 1.55 & 1.45 & 0.81 & 1.80 & 0.35 \\
EDTA23 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 23 & 3 & 1 & 6083 & 2.44 & 5.08 & 2.94 & 6.74 & 15.06 & 2.13 & 1.56 & 1.45 & 0.81 & 1.80 & 0.35 \\
EDTA24 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 24 & 3 & 1 & 6083 & 2.47 & 5.06 & 3.18 & 6.30 & 15.06 & 2.09 & 1.34 & 1.45 & 0.72 & 1.80 & 0.35 \\
EDTA25 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 25 & 3 & 1 & 6082 & 2.56 & 5.04 & 2.83 & 6.30 & 15.06 & 2.16 & 1.31 & 1.54 & 0.72 & 1.80 & 0.35 \\
EDTA26 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 26 & 3 & 1 & 6080 & 2.59 & 5.02 & 3.32 & 6.30 & 15.06 & 2.14 & 1.31 & 1.54 & 0.82 & 1.80 & 0.35 \\
EDTA27 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 27 & 3 & 1 & 6080 & 2.54 & 4.95 & 3.63 & 6.30 & 15.06 & 2.25 & 1.38 & 1.54 & 0.77 & 1.80 & 0.35 \\
EDTA28 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 28 & 3 & 1 & 6079 & 2.51 & 4.85 & 3.50 & 7.04 & 15.06 & 2.31 & 1.57 & 1.52 & 0.85 & 1.80 & 0.35 \\
EDTA29 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 29 & 3 & 1 & 6080 & 2.58 & 4.80 & 3.50 & 7.04 & 15.06 & 2.33 & 1.57 & 1.52 & 0.88 & 1.80 & 0.35 \\
EDTA30 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 30 & 3 & 1 & 6080 & 2.54 & 4.82 & 3.39 & 7.04 & 15.06 & 2.26 & 1.35 & 1.43 & 0.88 & 2.24 & 0.35 \\
EDTA31 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 31 & 3 & 1 & 6079 & 2.51 & 4.74 & 3.57 & 8.15 & 15.06 & 2.23 & 1.01 & 1.43 & 0.88 & 2.24 & 0.39 \\
EDTA32 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 32 & 3 & 1 & 6077 & 2.52 & 4.72 & 3.48 & 8.15 & 15.06 & 2.19 & 1.04 & 1.43 & 0.91 & 2.24 & 0.39 \\
EDTA33 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 33 & 3 & 1 & 6076 & 2.50 & 4.73 & 3.48 & 7.04 & 15.06 & 2.20 & 1.09 & 1.43 & 0.98 & 2.24 & 0.39 \\
EDTA34 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 34 & 3 & 1 & 6075 & 2.47 & 4.70 & 3.62 & 7.04 & 15.06 & 2.19 & 1.14 & 1.60 & 1.10 & 2.24 & 0.39 \\
EDTA35 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 35 & 3 & 1 & 6072 & 2.55 & 4.69 & 3.59 & 7.04 & 15.06 & 2.29 & 1.14 & 1.60 & 1.10 & 1.36 & 0.39 \\
EDTA36 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 36 & 3 & 1 & 6071 & 2.57 & 4.72 & 3.49 & 7.04 & 15.76 & 2.43 & 1.14 & 1.60 & 1.26 & 1.36 & 0.39 \\
EDTA37 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 37 & 3 & 1 & 6070 & 2.59 & 4.78 & 3.49 & 7.04 & 15.76 & 2.43 & 1.14 & 1.60 & 1.27 & 1.36 & 0.39 \\
EDTA38 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 38 & 3 & 1 & 6071 & 2.63 & 4.80 & 3.17 & 7.04 & 15.76 & 2.60 & 1.13 & 1.38 & 1.27 & 1.36 & 0.39 \\
EDTA39 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 39 & 3 & 1 & 6070 & 2.64 & 4.81 & 2.96 & 7.04 & 15.76 & 2.65 & 1.13 & 1.38 & 1.33 & 1.36 & 0.39 \\
EDTA40 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 40 & 3 & 1 & 6069 & 2.68 & 4.71 & 2.96 & 7.04 & 15.76 & 2.75 & 1.13 & 1.38 & 1.33 & 1.36 & 0.39 \\
EDTA41 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 41 & 3 & 1 & 6066 & 2.70 & 4.67 & 2.65 & 7.04 & 15.76 & 2.56 & 1.13 & 1.38 & 1.31 & 1.36 & 0.57 \\
EDTA42 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 42 & 3 & 1 & 6063 & 2.79 & 4.66 & 2.65 & 7.04 & 13.41 & 2.63 & 1.01 & 1.38 & 1.40 & 1.80 & 0.65 \\
EDTA43 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 43 & 3 & 1 & 6064 & 2.76 & 4.60 & 3.08 & 7.04 & 13.41 & 2.53 & 1.01 & 1.38 & 1.50 & 1.80 & 0.49 \\
EDTA44 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 44 & 3 & 1 & 6063 & 2.80 & 4.52 & 3.03 & 7.04 & 13.41 & 2.53 & 1.01 & 0.96 & 1.53 & 1.80 & 0.63 \\
EDTA45 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 45 & 3 & 1 & 6062 & 2.83 & 4.49 & 3.29 & 8.15 & 13.41 & 2.58 & 1.01 & 0.96 & 1.47 & 1.80 & 0.63 \\
EDTA46 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 46 & 3 & 1 & 6061 & 2.85 & 4.49 & 3.29 & 7.41 & 13.41 & 2.66 & 1.16 & 0.96 & 1.51 & 2.02 & 0.63 \\
EDTA47 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 47 & 3 & 1 & 6060 & 2.86 & 4.46 & 3.37 & 7.41 & 11.06 & 2.87 & 1.26 & 0.96 & 1.56 & 2.02 & 0.66 \\
EDTA48 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 48 & 3 & 1 & 6058 & 2.84 & 4.48 & 3.37 & 7.41 & 11.06 & 3.02 & 1.26 & 0.96 & 1.56 & 2.02 & 0.66 \\
EDTA49 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 49 & 3 & 1 & 6057 & 2.74 & 4.37 & 3.68 & 7.41 & 11.06 & 3.13 & 1.26 & 0.95 & 1.65 & 2.02 & 0.80 \\
EDTA50 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 50 & 3 & 1 & 6053 & 2.74 & 4.38 & 3.50 & 8.89 & 11.06 & 3.31 & 1.26 & 1.21 & 1.76 & 2.02 & 0.62 \\
EDTA51 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 51 & 3 & 1 & 6054 & 2.72 & 4.33 & 3.68 & 8.89 & 11.06 & 3.25 & 1.01 & 1.21 & 1.73 & 1.69 & 0.62 \\
EDTA52 & HRS IN ACADEMICS IN NON-JC PRGRMS IN WEEK 52 & 3 & 1 & 6053 & 2.72 & 4.31 & 4.03 & 8.89 & 11.06 & 3.15 & 1.01 & 1.21 & 1.68 & 1.69 & 0.62 \\
EDTV1 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 1 & 3 & 1 & 5759 & 0.33 & 0.25 & 0.12 & 1.30 & 0.00 & 0.36 & 0.72 & 0.00 & 0.16 & 0.00 & 0.22 \\
EDTV2 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 2 & 3 & 1 & 5766 & 0.45 & 0.40 & 0.49 & 2.78 & 2.56 & 0.37 & 0.57 & 0.00 & 0.53 & 0.91 & 0.40 \\
EDTV3 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 3 & 3 & 1 & 5770 & 0.55 & 0.46 & 0.44 & 2.96 & 4.78 & 0.34 & 0.79 & 0.00 & 0.47 & 0.91 & 0.57 \\
EDTV4 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 4 & 3 & 1 & 5769 & 0.54 & 0.49 & 0.44 & 4.44 & 4.78 & 0.27 & 0.54 & 0.53 & 0.44 & 0.91 & 0.57 \\
EDTV5 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 5 & 3 & 1 & 5765 & 0.54 & 0.51 & 0.58 & 2.96 & 4.78 & 0.27 & 0.54 & 0.53 & 0.43 & 0.00 & 0.40 \\
EDTV6 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 6 & 3 & 1 & 5766 & 0.53 & 0.53 & 0.58 & 2.96 & 4.78 & 0.23 & 0.54 & 0.53 & 0.38 & 0.00 & 0.22 \\
EDTV7 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 7 & 3 & 1 & 5766 & 0.59 & 0.52 & 0.58 & 3.70 & 2.22 & 0.25 & 0.54 & 0.53 & 0.38 & 0.00 & 0.04 \\
EDTV8 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 8 & 3 & 1 & 5766 & 0.59 & 0.56 & 0.58 & 3.89 & 2.22 & 0.25 & 0.54 & 0.53 & 0.38 & 0.00 & 0.04 \\
EDTV9 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 9 & 3 & 1 & 5767 & 0.56 & 0.62 & 0.58 & 3.89 & 2.22 & 0.26 & 0.54 & 0.00 & 0.38 & 0.00 & 0.04 \\
EDTV10 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 10 & 3 & 1 & 5768 & 0.56 & 0.64 & 0.58 & 3.89 & 2.22 & 0.27 & 0.54 & 0.00 & 0.38 & 0.00 & 0.04 \\
EDTV11 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 11 & 3 & 1 & 5768 & 0.59 & 0.62 & 0.58 & 3.89 & 2.22 & 0.29 & 0.54 & 0.00 & 0.31 & 0.00 & 0.04 \\
EDTV12 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 12 & 3 & 1 & 5768 & 0.61 & 0.71 & 0.58 & 3.89 & 2.22 & 0.30 & 0.32 & 0.00 & 0.16 & 0.00 & 0.04 \\
EDTV13 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 13 & 3 & 1 & 5766 & 0.56 & 0.75 & 0.46 & 3.89 & 2.22 & 0.30 & 0.36 & 0.00 & 0.16 & 0.00 & 0.02 \\
EDTV14 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 14 & 3 & 1 & 5765 & 0.57 & 0.76 & 0.62 & 3.89 & 2.22 & 0.30 & 0.36 & 0.00 & 0.23 & 0.00 & 0.04 \\
EDTV15 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 15 & 3 & 1 & 5764 & 0.62 & 0.77 & 0.62 & 3.89 & 2.22 & 0.36 & 0.36 & 0.00 & 0.23 & 0.00 & 0.04 \\
EDTV16 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 16 & 3 & 1 & 5764 & 0.60 & 0.82 & 0.62 & 2.41 & 2.22 & 0.30 & 0.36 & 0.00 & 0.27 & 0.00 & 0.04 \\
EDTV17 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 17 & 3 & 1 & 5764 & 0.60 & 0.86 & 0.62 & 2.41 & 2.22 & 0.28 & 0.36 & 0.00 & 0.22 & 0.00 & 0.04 \\
EDTV18 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 18 & 3 & 1 & 5765 & 0.57 & 0.90 & 0.62 & 2.41 & 4.44 & 0.28 & 0.11 & 0.00 & 0.13 & 0.00 & 0.04 \\
EDTV19 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 19 & 3 & 1 & 5764 & 0.56 & 0.94 & 0.62 & 2.41 & 4.44 & 0.28 & 0.11 & 0.00 & 0.13 & 0.00 & 0.04 \\
EDTV20 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 20 & 3 & 1 & 5761 & 0.59 & 0.95 & 0.87 & 2.41 & 4.44 & 0.37 & 0.11 & 0.00 & 0.19 & 0.00 & 0.04 \\
EDTV21 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 21 & 3 & 1 & 5760 & 0.63 & 0.99 & 1.21 & 2.41 & 4.44 & 0.44 & 0.11 & 0.00 & 0.19 & 0.00 & 0.04 \\
EDTV22 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 22 & 3 & 1 & 5760 & 0.64 & 0.96 & 1.41 & 2.41 & 4.44 & 0.51 & 0.11 & 0.00 & 0.19 & 0.00 & 0.04 \\
EDTV23 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 23 & 3 & 1 & 5760 & 0.67 & 0.92 & 1.41 & 2.41 & 4.44 & 0.58 & 0.11 & 0.00 & 0.19 & 0.00 & 0.04 \\
EDTV24 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 24 & 3 & 1 & 5758 & 0.68 & 0.93 & 1.41 & 2.41 & 4.44 & 0.53 & 0.11 & 0.00 & 0.19 & 0.00 & 0.04 \\
EDTV25 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 25 & 3 & 1 & 5758 & 0.68 & 0.94 & 1.41 & 2.41 & 4.44 & 0.70 & 0.21 & 0.00 & 0.16 & 0.00 & 0.04 \\
EDTV26 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 26 & 3 & 1 & 5757 & 0.68 & 0.96 & 1.41 & 2.41 & 4.44 & 0.70 & 0.21 & 0.00 & 0.22 & 0.00 & 0.04 \\
EDTV27 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 27 & 3 & 1 & 5756 & 0.69 & 0.93 & 1.22 & 2.41 & 4.44 & 0.79 & 0.21 & 0.00 & 0.31 & 0.00 & 0.04 \\
EDTV28 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 28 & 3 & 1 & 5756 & 0.73 & 0.93 & 1.22 & 2.41 & 4.44 & 0.75 & 0.21 & 0.00 & 0.36 & 0.00 & 0.04 \\
EDTV29 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 29 & 3 & 1 & 5755 & 0.75 & 0.94 & 1.22 & 2.41 & 4.44 & 0.77 & 0.21 & 0.00 & 0.36 & 0.00 & 0.04 \\
EDTV30 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 30 & 3 & 1 & 5753 & 0.76 & 0.95 & 1.22 & 2.41 & 4.44 & 0.82 & 0.21 & 0.00 & 0.36 & 0.00 & 0.04 \\
EDTV31 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 31 & 3 & 1 & 5753 & 0.75 & 0.94 & 1.22 & 2.41 & 4.44 & 0.84 & 0.17 & 0.00 & 0.36 & 0.00 & 0.15 \\
EDTV32 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 32 & 3 & 1 & 5753 & 0.72 & 0.94 & 0.97 & 2.41 & 4.44 & 0.77 & 0.17 & 0.12 & 0.37 & 0.00 & 0.15 \\
EDTV33 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 33 & 3 & 1 & 5752 & 0.73 & 0.93 & 0.97 & 2.41 & 4.44 & 0.77 & 0.17 & 0.12 & 0.36 & 0.00 & 0.15 \\
EDTV34 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 34 & 3 & 1 & 5753 & 0.78 & 0.90 & 0.97 & 2.41 & 4.44 & 0.77 & 0.17 & 0.12 & 0.38 & 0.00 & 0.15 \\
EDTV35 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 35 & 3 & 1 & 5753 & 0.78 & 0.98 & 0.97 & 2.41 & 4.44 & 0.77 & 0.17 & 0.12 & 0.32 & 0.00 & 0.15 \\
EDTV36 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 36 & 3 & 1 & 5754 & 0.73 & 0.98 & 0.97 & 2.41 & 4.44 & 0.72 & 0.17 & 0.12 & 0.38 & 0.00 & 0.15 \\
EDTV37 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 37 & 3 & 1 & 5753 & 0.68 & 0.96 & 0.97 & 2.41 & 4.44 & 0.67 & 0.17 & 0.12 & 0.38 & 0.00 & 0.15 \\
EDTV38 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 38 & 3 & 1 & 5750 & 0.65 & 1.00 & 0.97 & 2.41 & 4.44 & 0.78 & 0.17 & 0.00 & 0.52 & 0.00 & 0.15 \\
EDTV39 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 39 & 3 & 1 & 5750 & 0.67 & 0.99 & 0.97 & 2.41 & 4.44 & 0.77 & 0.17 & 0.00 & 0.56 & 0.00 & 0.15 \\
EDTV40 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 40 & 3 & 1 & 5746 & 0.72 & 1.02 & 0.97 & 2.41 & 4.44 & 0.77 & 0.17 & 0.00 & 0.58 & 0.00 & 0.15 \\
EDTV41 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 41 & 3 & 1 & 5746 & 0.73 & 1.05 & 0.97 & 2.41 & 4.44 & 0.75 & 0.17 & 0.00 & 0.59 & 0.00 & 0.18 \\
EDTV42 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 42 & 3 & 1 & 5746 & 0.79 & 1.06 & 0.97 & 2.41 & 4.44 & 0.74 & 0.17 & 0.00 & 0.67 & 0.00 & 0.18 \\
EDTV43 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 43 & 3 & 1 & 5746 & 0.79 & 1.05 & 0.98 & 2.41 & 4.44 & 0.64 & 0.17 & 0.00 & 0.67 & 0.00 & 0.16 \\
EDTV44 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 44 & 3 & 1 & 5743 & 0.79 & 1.10 & 1.14 & 2.41 & 2.22 & 0.64 & 0.17 & 0.00 & 0.70 & 0.00 & 0.16 \\
EDTV45 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 45 & 3 & 1 & 5744 & 0.80 & 1.12 & 1.14 & 3.52 & 2.22 & 0.64 & 0.17 & 0.00 & 0.64 & 0.00 & 0.16 \\
EDTV46 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 46 & 3 & 1 & 5746 & 0.86 & 1.14 & 1.14 & 3.52 & 2.22 & 0.57 & 0.17 & 0.00 & 0.65 & 0.00 & 0.16 \\
EDTV47 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 47 & 3 & 1 & 5745 & 0.86 & 1.13 & 1.48 & 3.52 & 0.00 & 0.62 & 0.17 & 0.00 & 0.73 & 0.00 & 0.16 \\
EDTV48 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 48 & 3 & 1 & 5745 & 0.80 & 1.09 & 1.48 & 3.52 & 0.00 & 0.69 & 0.17 & 0.00 & 0.68 & 0.00 & 0.16 \\
EDTV49 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 49 & 3 & 1 & 5744 & 0.77 & 1.03 & 1.48 & 3.52 & 0.00 & 0.66 & 0.17 & 0.00 & 0.68 & 0.00 & 0.16 \\
EDTV50 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 50 & 3 & 1 & 5743 & 0.77 & 0.99 & 1.48 & 3.52 & 0.00 & 0.66 & 0.17 & 0.00 & 0.61 & 0.00 & 0.13 \\
EDTV51 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 51 & 3 & 1 & 5742 & 0.79 & 0.97 & 1.52 & 3.52 & 0.00 & 0.67 & 0.17 & 0.00 & 0.63 & 0.00 & 0.13 \\
EDTV52 & HRS IN VOC TRNG IN NON-JC PRGRMS IN WEEK 52 & 3 & 1 & 5742 & 0.91 & 0.96 & 1.57 & 3.52 & 0.00 & 0.67 & 0.17 & 0.00 & 0.64 & 0.00 & 0.13 \\
AFDCH1 & GOT AFDC IN MONTH 1 & 1 & 1 & 1098 & 0.25 & 0.23 & 0.28 & 0.50 & 0.18 & 0.25 & 0.27 & 0.14 & 0.22 & 0.34 & 0.20 \\
AFDCH2 & GOT AFDC IN MONTH 2 & 1 & 1 & 550 & 0.16 & 0.14 & 0.17 & 0.38 & 0.10 & 0.15 & 0.17 & 0.07 & 0.12 & 0.17 & 0.12 \\
AFDCH3 & GOT AFDC IN MONTH 3 & 1 & 1 & 517 & 0.15 & 0.13 & 0.18 & 0.36 & 0.10 & 0.14 & 0.16 & 0.07 & 0.12 & 0.15 & 0.11 \\
AFDCH4 & GOT AFDC IN MONTH 4 & 1 & 1 & 506 & 0.15 & 0.13 & 0.18 & 0.36 & 0.10 & 0.14 & 0.16 & 0.07 & 0.12 & 0.14 & 0.11 \\
AFDCH5 & GOT AFDC IN MONTH 5 & 1 & 1 & 501 & 0.15 & 0.13 & 0.19 & 0.36 & 0.10 & 0.13 & 0.16 & 0.07 & 0.11 & 0.14 & 0.11 \\
AFDCH6 & GOT AFDC IN MONTH 6 & 1 & 1 & 499 & 0.15 & 0.13 & 0.19 & 0.33 & 0.15 & 0.14 & 0.15 & 0.07 & 0.11 & 0.14 & 0.11 \\
AFDCH7 & GOT AFDC IN MONTH 7 & 1 & 1 & 498 & 0.15 & 0.13 & 0.18 & 0.33 & 0.15 & 0.14 & 0.15 & 0.07 & 0.11 & 0.14 & 0.11 \\
AFDCH8 & GOT AFDC IN MONTH 8 & 1 & 1 & 495 & 0.15 & 0.13 & 0.19 & 0.31 & 0.15 & 0.14 & 0.15 & 0.07 & 0.11 & 0.14 & 0.11 \\
AFDCH9 & GOT AFDC IN MONTH 9 & 1 & 1 & 489 & 0.15 & 0.13 & 0.19 & 0.31 & 0.15 & 0.14 & 0.15 & 0.07 & 0.11 & 0.14 & 0.11 \\
AFDCH10 & GOT AFDC IN MONTH 10 & 1 & 1 & 483 & 0.15 & 0.13 & 0.19 & 0.31 & 0.15 & 0.14 & 0.15 & 0.07 & 0.11 & 0.14 & 0.11 \\
AFDCH11 & GOT AFDC IN MONTH 11 & 1 & 1 & 478 & 0.15 & 0.13 & 0.19 & 0.31 & 0.12 & 0.15 & 0.15 & 0.07 & 0.11 & 0.14 & 0.11 \\
AFDCH12 & GOT AFDC IN MONTH 12 & 1 & 1 & 479 & 0.16 & 0.13 & 0.20 & 0.31 & 0.12 & 0.14 & 0.15 & 0.07 & 0.11 & 0.15 & 0.11 \\
FSH1 & GOT FOOD STAMPS IN MONTH 1 & 1 & 1 & 777 & 0.35 & 0.31 & 0.39 & 0.48 & 0.31 & 0.33 & 0.34 & 0.25 & 0.28 & 0.34 & 0.26 \\
FSH2 & GOT FOOD STAMPS IN MONTH 2 & 1 & 1 & 414 & 0.21 & 0.17 & 0.22 & 0.35 & 0.14 & 0.16 & 0.20 & 0.10 & 0.14 & 0.19 & 0.13 \\
FSH3 & GOT FOOD STAMPS IN MONTH 3 & 1 & 1 & 381 & 0.19 & 0.16 & 0.23 & 0.33 & 0.10 & 0.15 & 0.18 & 0.09 & 0.13 & 0.18 & 0.13 \\
FSH4 & GOT FOOD STAMPS IN MONTH 4 & 1 & 1 & 378 & 0.19 & 0.16 & 0.22 & 0.37 & 0.10 & 0.15 & 0.17 & 0.08 & 0.13 & 0.16 & 0.13 \\
FSH5 & GOT FOOD STAMPS IN MONTH 5 & 1 & 1 & 372 & 0.20 & 0.16 & 0.22 & 0.37 & 0.12 & 0.15 & 0.17 & 0.08 & 0.13 & 0.17 & 0.13 \\
FSH6 & GOT FOOD STAMPS IN MONTH 6 & 1 & 1 & 373 & 0.19 & 0.16 & 0.23 & 0.37 & 0.14 & 0.15 & 0.17 & 0.08 & 0.13 & 0.18 & 0.13 \\
FSH7 & GOT FOOD STAMPS IN MONTH 7 & 1 & 1 & 378 & 0.19 & 0.16 & 0.23 & 0.37 & 0.17 & 0.15 & 0.17 & 0.08 & 0.13 & 0.17 & 0.13 \\
FSH8 & GOT FOOD STAMPS IN MONTH 8 & 1 & 1 & 377 & 0.20 & 0.17 & 0.23 & 0.35 & 0.17 & 0.16 & 0.17 & 0.08 & 0.14 & 0.17 & 0.13 \\
FSH9 & GOT FOOD STAMPS IN MONTH 9 & 1 & 1 & 374 & 0.20 & 0.17 & 0.23 & 0.35 & 0.17 & 0.16 & 0.17 & 0.08 & 0.14 & 0.17 & 0.13 \\
FSH10 & GOT FOOD STAMPS IN MONTH 10 & 1 & 1 & 373 & 0.21 & 0.17 & 0.24 & 0.42 & 0.17 & 0.16 & 0.17 & 0.08 & 0.14 & 0.17 & 0.13 \\
FSH11 & GOT FOOD STAMPS IN MONTH 11 & 1 & 1 & 370 & 0.21 & 0.17 & 0.24 & 0.42 & 0.17 & 0.17 & 0.18 & 0.09 & 0.15 & 0.18 & 0.13 \\
FSH12 & GOT FOOD STAMPS IN MONTH 12 & 1 & 1 & 368 & 0.21 & 0.17 & 0.25 & 0.42 & 0.14 & 0.18 & 0.17 & 0.10 & 0.15 & 0.18 & 0.13 \\
SSIH1 & GOT SSI/SSA IN MONTH 1 & 1 & 1 & 355 & 0.05 & 0.06 & 0.05 & 0.07 & 0.05 & 0.05 & 0.04 & 0.05 & 0.04 & 0.02 & 0.02 \\
SSIH2 & GOT SSI/SSA IN MONTH 2 & 1 & 1 & 355 & 0.05 & 0.06 & 0.06 & 0.07 & 0.05 & 0.06 & 0.04 & 0.06 & 0.04 & 0.02 & 0.02 \\
SSIH3 & GOT SSI/SSA IN MONTH 3 & 1 & 1 & 355 & 0.05 & 0.06 & 0.05 & 0.07 & 0.05 & 0.06 & 0.04 & 0.06 & 0.04 & 0.02 & 0.02 \\
SSIH4 & GOT SSI/SSA IN MONTH 4 & 1 & 1 & 356 & 0.05 & 0.06 & 0.05 & 0.07 & 0.05 & 0.06 & 0.04 & 0.06 & 0.04 & 0.02 & 0.02 \\
SSIH5 & GOT SSI/SSA IN MONTH 5 & 1 & 1 & 355 & 0.05 & 0.06 & 0.05 & 0.07 & 0.05 & 0.06 & 0.04 & 0.06 & 0.04 & 0.02 & 0.02 \\
SSIH6 & GOT SSI/SSA IN MONTH 6 & 1 & 1 & 355 & 0.05 & 0.06 & 0.05 & 0.09 & 0.05 & 0.06 & 0.04 & 0.06 & 0.04 & 0.02 & 0.02 \\
SSIH7 & GOT SSI/SSA IN MONTH 7 & 1 & 1 & 354 & 0.05 & 0.06 & 0.06 & 0.09 & 0.05 & 0.06 & 0.05 & 0.06 & 0.04 & 0.02 & 0.02 \\
SSIH8 & GOT SSI/SSA IN MONTH 8 & 1 & 1 & 354 & 0.05 & 0.06 & 0.06 & 0.09 & 0.05 & 0.06 & 0.05 & 0.06 & 0.04 & 0.02 & 0.02 \\
SSIH9 & GOT SSI/SSA IN MONTH 9 & 1 & 1 & 353 & 0.05 & 0.06 & 0.06 & 0.09 & 0.05 & 0.06 & 0.05 & 0.06 & 0.04 & 0.02 & 0.02 \\
SSIH10 & GOT SSI/SSA IN MONTH 10 & 1 & 1 & 352 & 0.05 & 0.06 & 0.06 & 0.09 & 0.05 & 0.06 & 0.05 & 0.06 & 0.04 & 0.02 & 0.02 \\
SSIH11 & GOT SSI/SSA IN MONTH 11 & 1 & 1 & 351 & 0.05 & 0.06 & 0.06 & 0.09 & 0.05 & 0.06 & 0.04 & 0.05 & 0.04 & 0.02 & 0.02 \\
SSIH12 & GOT SSI/SSA IN MONTH 12 & 1 & 1 & 352 & 0.05 & 0.06 & 0.06 & 0.09 & 0.05 & 0.06 & 0.04 & 0.05 & 0.04 & 0.01 & 0.02 \\
GAH1 & GOT GENERAL ASSIST. IN MONTH 1 & 1 & 1 & 409 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 \\
GAH2 & GOT GENERAL ASSIST. IN MONTH 2 & 1 & 1 & 414 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.01 \\
GAH3 & GOT GENERAL ASSIST. IN MONTH 3 & 1 & 1 & 415 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.01 \\
GAH4 & GOT GENERAL ASSIST. IN MONTH 4 & 1 & 1 & 414 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.02 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 \\
GAH5 & GOT GENERAL ASSIST. IN MONTH 5 & 1 & 1 & 414 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 \\
GAH6 & GOT GENERAL ASSIST. IN MONTH 6 & 1 & 1 & 414 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 \\
GAH7 & GOT GENERAL ASSIST. IN MONTH 7 & 1 & 1 & 414 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 \\
GAH8 & GOT GENERAL ASSIST. IN MONTH 8 & 1 & 1 & 414 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.01 \\
GAH9 & GOT GENERAL ASSIST. IN MONTH 9 & 1 & 1 & 415 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.01 \\
GAH10 & GOT GENERAL ASSIST. IN MONTH 10 & 1 & 1 & 415 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 & 0.00 & 0.01 \\
GAH11 & GOT GENERAL ASSIST. IN MONTH 11 & 1 & 1 & 414 & 0.01 & 0.01 & 0.03 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.01 & 0.01 \\
GAH12 & GOT GENERAL ASSIST. IN MONTH 12 & 1 & 1 & 415 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 & 0.01 \\
ANYPH1 & GOT AFDC/FS/GA/SSI IN MONTH 1 & 1 & 1 & 1082 & 0.41 & 0.39 & 0.46 & 0.59 & 0.38 & 0.40 & 0.44 & 0.31 & 0.35 & 0.43 & 0.31 \\
ANYPH2 & GOT AFDC/FS/GA/SSI IN MONTH 2 & 1 & 1 & 645 & 0.27 & 0.25 & 0.30 & 0.50 & 0.20 & 0.24 & 0.28 & 0.17 & 0.20 & 0.25 & 0.17 \\
ANYPH3 & GOT AFDC/FS/GA/SSI IN MONTH 3 & 1 & 1 & 622 & 0.27 & 0.24 & 0.30 & 0.48 & 0.17 & 0.23 & 0.26 & 0.16 & 0.19 & 0.23 & 0.17 \\
ANYPH4 & GOT AFDC/FS/GA/SSI IN MONTH 4 & 1 & 1 & 615 & 0.26 & 0.24 & 0.30 & 0.50 & 0.17 & 0.23 & 0.26 & 0.15 & 0.19 & 0.21 & 0.17 \\
ANYPH5 & GOT AFDC/FS/GA/SSI IN MONTH 5 & 1 & 1 & 610 & 0.27 & 0.24 & 0.30 & 0.50 & 0.20 & 0.23 & 0.25 & 0.15 & 0.18 & 0.22 & 0.16 \\
ANYPH6 & GOT AFDC/FS/GA/SSI IN MONTH 6 & 1 & 1 & 610 & 0.26 & 0.24 & 0.31 & 0.50 & 0.24 & 0.23 & 0.25 & 0.16 & 0.19 & 0.22 & 0.16 \\
ANYPH7 & GOT AFDC/FS/GA/SSI IN MONTH 7 & 1 & 1 & 607 & 0.26 & 0.24 & 0.30 & 0.50 & 0.27 & 0.23 & 0.25 & 0.16 & 0.19 & 0.22 & 0.16 \\
ANYPH8 & GOT AFDC/FS/GA/SSI IN MONTH 8 & 1 & 1 & 606 & 0.27 & 0.25 & 0.31 & 0.48 & 0.27 & 0.24 & 0.25 & 0.16 & 0.19 & 0.22 & 0.16 \\
ANYPH9 & GOT AFDC/FS/GA/SSI IN MONTH 9 & 1 & 1 & 600 & 0.27 & 0.25 & 0.31 & 0.48 & 0.27 & 0.24 & 0.25 & 0.16 & 0.19 & 0.22 & 0.17 \\
ANYPH10 & GOT AFDC/FS/GA/SSI IN MONTH 10 & 1 & 1 & 597 & 0.28 & 0.25 & 0.32 & 0.55 & 0.27 & 0.24 & 0.26 & 0.15 & 0.19 & 0.22 & 0.16 \\
ANYPH11 & GOT AFDC/FS/GA/SSI IN MONTH 11 & 1 & 1 & 587 & 0.28 & 0.25 & 0.32 & 0.55 & 0.27 & 0.25 & 0.25 & 0.15 & 0.20 & 0.23 & 0.17 \\
ANYPH12 & GOT AFDC/FS/GA/SSI IN MONTH 12 & 1 & 1 & 588 & 0.28 & 0.25 & 0.33 & 0.55 & 0.24 & 0.25 & 0.25 & 0.16 & 0.21 & 0.23 & 0.17 \\
WICH1 & GOT WIC IN MONTH 1 & 1 & 1 & 6484 & 0.16 & 0.13 & 0.15 & 0.21 & 0.20 & 0.12 & 0.17 & 0.10 & 0.12 & 0.18 & 0.14 \\
WICH2 & GOT WIC IN MONTH 2 & 1 & 1 & 6588 & 0.18 & 0.15 & 0.16 & 0.21 & 0.20 & 0.13 & 0.18 & 0.11 & 0.12 & 0.18 & 0.14 \\
WICH3 & GOT WIC IN MONTH 3 & 1 & 1 & 6600 & 0.18 & 0.16 & 0.17 & 0.21 & 0.20 & 0.14 & 0.18 & 0.11 & 0.13 & 0.18 & 0.14 \\
WICH4 & GOT WIC IN MONTH 4 & 1 & 1 & 6606 & 0.19 & 0.16 & 0.17 & 0.25 & 0.20 & 0.14 & 0.18 & 0.11 & 0.13 & 0.18 & 0.14 \\
WICH5 & GOT WIC IN MONTH 5 & 1 & 1 & 6609 & 0.19 & 0.16 & 0.19 & 0.25 & 0.20 & 0.14 & 0.18 & 0.11 & 0.13 & 0.18 & 0.15 \\
WICH6 & GOT WIC IN MONTH 6 & 1 & 1 & 6612 & 0.20 & 0.17 & 0.18 & 0.25 & 0.20 & 0.15 & 0.18 & 0.11 & 0.13 & 0.18 & 0.15 \\
WICH7 & GOT WIC IN MONTH 7 & 1 & 1 & 6613 & 0.20 & 0.17 & 0.19 & 0.21 & 0.20 & 0.15 & 0.18 & 0.11 & 0.14 & 0.18 & 0.14 \\
WICH8 & GOT WIC IN MONTH 8 & 1 & 1 & 6611 & 0.20 & 0.17 & 0.21 & 0.25 & 0.20 & 0.15 & 0.19 & 0.11 & 0.14 & 0.18 & 0.14 \\
WICH9 & GOT WIC IN MONTH 9 & 1 & 1 & 6611 & 0.20 & 0.17 & 0.21 & 0.29 & 0.20 & 0.16 & 0.19 & 0.12 & 0.14 & 0.18 & 0.14 \\
WICH10 & GOT WIC IN MONTH 10 & 1 & 1 & 6611 & 0.20 & 0.18 & 0.22 & 0.29 & 0.20 & 0.16 & 0.21 & 0.12 & 0.14 & 0.18 & 0.14 \\
WICH11 & GOT WIC IN MONTH 11 & 1 & 1 & 6612 & 0.21 & 0.18 & 0.22 & 0.29 & 0.20 & 0.17 & 0.21 & 0.11 & 0.14 & 0.18 & 0.14 \\
WICH12 & GOT WIC IN MONTH 12 & 1 & 1 & 6612 & 0.21 & 0.19 & 0.22 & 0.29 & 0.20 & 0.17 & 0.21 & 0.11 & 0.15 & 0.16 & 0.14 \\
f_f23 & marital status & 2 & 1 & 580 & 1.34 & 1.26 & 1.35 & 1.16 & 1.30 & 1.29 & 1.18 & 1.18 & 1.32 & 1.08 & 1.18 \\
f_g78 & resp & kids covered by publ hlth insur & 2 & 1 & 1130 & 0.54 & 0.52 & 0.51 & 0.64 & 0.29 & 0.54 & 0.53 & 0.51 & 0.47 & 0.60 & 0.60 \\
f_g80 & int chk: rspndt lives in jc/institution & 1 & 1 & 832 & 0.06 & 0.03 & 0.03 & 0.10 & 0.20 & 0.02 & 0.34 & 0.39 & 0.02 & 0.27 & 0.37 \\
f_g81 & 1/0 respondent lives in public housing & 1 & 1 & 1564 & 0.17 & 0.17 & 0.20 & 0.28 & 0.12 & 0.19 & 0.25 & 0.18 & 0.13 & 0.27 & 0.16 \\
f_g82 & 1/2 respondent owns or rents home & 1 & 1 & 3725 & 1.64 & 1.63 & 1.55 & 1.52 & 1.42 & 1.61 & 1.64 & 1.64 & 1.61 & 1.66 & 1.58 \\
evarrq1 & ever arrested in qtr 1 & 1 & 1 & 89 & 0.03 & 0.04 & 0.02 & 0.05 & 0.02 & 0.01 & 0.01 & 0.02 & 0.02 & 0.01 & 0.02 \\
evarrq2 & ever arrested in qtr 2 & 1 & 1 & 87 & 0.03 & 0.04 & 0.02 & 0.05 & 0.07 & 0.03 & 0.01 & 0.02 & 0.03 & 0.00 & 0.01 \\
evarrq3 & ever arrested in qtr 3 & 1 & 1 & 89 & 0.04 & 0.05 & 0.03 & 0.02 & 0.02 & 0.04 & 0.02 & 0.02 & 0.03 & 0.04 & 0.01 \\
evarrq4 & ever arrested in qtr 4 & 1 & 1 & 84 & 0.05 & 0.05 & 0.03 & 0.07 & 0.12 & 0.05 & 0.01 & 0.02 & 0.04 & 0.00 & 0.01 \\
narry1 & number of arrests in year 1 & 3 & 1 & 99 & 0.20 & 0.23 & 0.11 & 0.23 & 0.29 & 0.18 & 0.06 & 0.07 & 0.15 & 0.06 & 0.04 \\
narc1_1 & \# arrests yr 1: chrged w/murder & 3 & 1 & 99 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
narc1_2 & \# arrests yr 1: chrged w/agg. assault & 3 & 1 & 99 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 \\
narc1_3 & \# arrests yr 1: chrged w/robbery & 3 & 1 & 99 & 0.01 & 0.01 & 0.01 & 0.00 & 0.00 & 0.01 & 0.00 & 0.01 & 0.01 & 0.01 & 0.00 \\
narc1_4 & \# arrests yr 1: chrged w/burglary & 3 & 1 & 99 & 0.01 & 0.02 & 0.00 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 & 0.01 & 0.01 & 0.00 \\
narc1_5 & \# arrests yr 1: chrged w/theft & 3 & 1 & 99 & 0.03 & 0.04 & 0.03 & 0.07 & 0.12 & 0.03 & 0.01 & 0.02 & 0.03 & 0.02 & 0.01 \\
narc1_6 & \# arrests yr 1: chrged w/drug viol. & 3 & 1 & 99 & 0.02 & 0.03 & 0.01 & 0.05 & 0.02 & 0.02 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 \\
narc1_7 & \# arrests yr 1: chrged w/oth personal & 3 & 1 & 99 & 0.02 & 0.02 & 0.01 & 0.00 & 0.02 & 0.01 & 0.01 & 0.00 & 0.02 & 0.00 & 0.00 \\
narc1_8 & \# arrests yr 1: chrged w/oth misc crimes & 3 & 1 & 99 & 0.09 & 0.10 & 0.03 & 0.09 & 0.10 & 0.07 & 0.03 & 0.03 & 0.06 & 0.01 & 0.02 \\
anycra12 & any crimes against resp: 12mi & 1 & 1 & 605 & 0.23 & 0.24 & 0.21 & 0.16 & 0.28 & 0.22 & 0.14 & 0.16 & 0.24 & 0.16 & 0.19 \\
moneya12 & amt money respt lost from crimes in py & 3 & 1 & 621 & 117.84 & 130.61 & 79.78 & 173.91 & 273.10 & 122.15 & 63.56 & 36.74 & 112.17 & 100.87 & 58.91 \\
numvic12 & \# times victimized: 12m int & 3 & 1 & 664 & 0.53 & 0.60 & 0.52 & 0.51 & 0.45 & 0.54 & 0.25 & 0.37 & 0.60 & 0.23 & 0.50 \\
numcra12 & total \# crimes agnst resp in py: 12m & 3 & 1 & 608 & 0.43 & 0.53 & 0.43 & 0.48 & 0.37 & 0.46 & 0.22 & 0.32 & 0.50 & 0.23 & 0.43 \\
carst12 & car was stolen: 12m int & 1 & 1 & 620 & 0.02 & 0.02 & 0.02 & 0.05 & 0.00 & 0.02 & 0.00 & 0.02 & 0.01 & 0.01 & 0.01 \\
burgd12 & home was burglarized: 12m int & 1 & 1 & 619 & 0.05 & 0.05 & 0.02 & 0.02 & 0.00 & 0.05 & 0.03 & 0.01 & 0.04 & 0.04 & 0.02 \\
assld12 & r assaulted (aggravated) & 1 & 1 & 614 & 0.10 & 0.10 & 0.12 & 0.05 & 0.15 & 0.09 & 0.05 & 0.05 & 0.10 & 0.05 & 0.06 \\
robbd12 & r robbed: 12m int & 1 & 1 & 615 & 0.06 & 0.07 & 0.05 & 0.09 & 0.05 & 0.07 & 0.04 & 0.05 & 0.06 & 0.03 & 0.05 \\
rippd12 & victim of theft/pickpoket/extortion & 1 & 1 & 617 & 0.07 & 0.09 & 0.06 & 0.09 & 0.10 & 0.08 & 0.06 & 0.05 & 0.10 & 0.06 & 0.10 \\
nassld12 & \# times r assaulted (aggravated): 12m & 3 & 1 & 614 & 0.25 & 0.22 & 0.34 & 0.05 & 0.22 & 0.20 & 0.08 & 0.14 & 0.25 & 0.08 & 0.12 \\
nburgd12 & \# times home was burglarized: 12m int & 3 & 1 & 619 & 0.07 & 0.07 & 0.03 & 0.02 & 0.00 & 0.06 & 0.04 & 0.02 & 0.05 & 0.06 & 0.05 \\
nrobbd12 & \# times r robbed: 12m int & 3 & 1 & 615 & 0.07 & 0.10 & 0.05 & 0.14 & 0.05 & 0.10 & 0.05 & 0.07 & 0.10 & 0.03 & 0.09 \\
nrippd12 & \# times victim of theft/pickp/extort:12m & 3 & 1 & 617 & 0.12 & 0.18 & 0.08 & 0.26 & 0.15 & 0.16 & 0.09 & 0.12 & 0.18 & 0.07 & 0.23 \\
ncarst12 & \# times car was stolen: 12m int & 3 & 1 & 620 & 0.02 & 0.02 & 0.02 & 0.05 & 0.00 & 0.02 & 0.00 & 0.02 & 0.02 & 0.03 & 0.02 \\
cig12 & smoked cigarettes in mnth bef 12m int & 1 & 1 & 587 & 0.50 & 0.50 & 0.51 & 0.37 & 0.45 & 0.51 & 0.48 & 0.40 & 0.55 & 0.44 & 0.51 \\
drink12 & drank alcohol in mnth bef 12 mnth int & 1 & 1 & 589 & 0.29 & 0.29 & 0.30 & 0.23 & 0.30 & 0.26 & 0.22 & 0.12 & 0.32 & 0.23 & 0.21 \\
pot12 & used pot in month bef 12m int & 1 & 1 & 592 & 0.09 & 0.09 & 0.12 & 0.07 & 0.10 & 0.12 & 0.05 & 0.05 & 0.10 & 0.03 & 0.05 \\
coke12 & used coke in mnth bef 12 mnth int & 1 & 1 & 588 & 0.00 & 0.00 & 0.01 & 0.05 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 \\
crack12 & used crack in mnth bef 12 mnth int & 1 & 1 & 589 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
heroin12 & used heroin in mnth bef 12m int & 1 & 1 & 588 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
speed12 & used speed in mnth bef 12m int & 1 & 1 & 591 & 0.00 & 0.01 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.01 \\
lsd12 & used lsd in mnth bef 12m int & 1 & 1 & 591 & 0.01 & 0.01 & 0.01 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.01 \\
inject12 & injected drugs in mnth bef 12m int & 1 & 1 & 590 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
othdrg12 & used oth drugs in mnth bef 12m int & 1 & 1 & 589 & 0.00 & 0.00 & 0.00 & 0.02 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 \\
fcig12 & freq smoked cigs in mnth bef 12m int & 2 & 1 & 597 & 2.40 & 2.38 & 2.38 & 2.05 & 2.28 & 2.42 & 2.29 & 2.09 & 2.56 & 2.21 & 2.42 \\
fpot12 & freq used pot in mnth bef 12m int & 2 & 1 & 594 & 1.18 & 1.19 & 1.25 & 1.21 & 1.23 & 1.28 & 1.10 & 1.10 & 1.22 & 1.07 & 1.09 \\
fcoke12 & freq used coke in mnth bef 12m int & 2 & 1 & 588 & 1.01 & 1.00 & 1.02 & 1.12 & 1.02 & 1.01 & 1.00 & 1.00 & 1.00 & 1.03 & 1.00 \\
fcrack12 & freq used crack in mnth bef 12m int & 2 & 1 & 589 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 \\
fhern12 & freq used heroin in mnth bef 12m int & 2 & 1 & 588 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 \\
fspeed12 & freq used speed in mnth bef 12m int & 2 & 1 & 591 & 1.00 & 1.01 & 1.00 & 1.07 & 1.00 & 1.01 & 1.00 & 1.00 & 1.01 & 1.00 & 1.01 \\
flsd12 & freq used lsd in mnth bef 12m int & 2 & 1 & 591 & 1.01 & 1.01 & 1.02 & 1.05 & 1.00 & 1.01 & 1.00 & 1.00 & 1.02 & 1.00 & 1.01 \\
finjct12 & freq injected drugs in mnth bef 12m int & 2 & 1 & 590 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 \\
fothdg12 & freq used oth drugs in mnth bef 12m int & 2 & 1 & 589 & 1.00 & 1.00 & 1.01 & 1.07 & 1.02 & 1.00 & 1.00 & 1.00 & 1.00 & 1.03 & 1.01 \\
hard12 & used hard drugs in mnth bef 12m int & 1 & 1 & 597 & 0.02 & 0.02 & 0.02 & 0.05 & 0.05 & 0.01 & 0.00 & 0.00 & 0.02 & 0.01 & 0.02 \\
anydr12 & used any drugs in mnth bef 12m int & 1 & 1 & 602 & 0.09 & 0.10 & 0.12 & 0.09 & 0.12 & 0.13 & 0.05 & 0.05 & 0.11 & 0.04 & 0.05 \\
fdrink12 & freq drank alcohol in mnth bef 12m int & 2 & 1 & 595 & 1.44 & 1.45 & 1.49 & 1.30 & 1.42 & 1.42 & 1.33 & 1.16 & 1.51 & 1.32 & 1.29 \\
health12 & 1=exc health 2=good 3=fair 4=poor & 2 & 1 & 597 & 1.77 & 1.81 & 1.82 & 2.02 & 1.78 & 1.78 & 1.83 & 1.70 & 1.74 & 1.69 & 1.69 \\
pe_prb12 & 1=phys/emot probs at 12 mths 0=no prob & 1 & 1 & 597 & 0.13 & 0.14 & 0.14 & 0.05 & 0.12 & 0.13 & 0.11 & 0.13 & 0.14 & 0.08 & 0.13 \\
whoursy1 & cc hours/wk, all types in yr 1 & 3 & 1 & 109 & 3.89 & 2.98 & 3.94 & 5.75 & 4.68 & 4.02 & 4.23 & 3.88 & 5.23 & 3.66 & 5.39 \\
eparent1 & cc by parents in yr 1 & 1 & 1 & 38 & 0.07 & 0.07 & 0.09 & 0.02 & 0.05 & 0.08 & 0.05 & 0.06 & 0.09 & 0.06 & 0.05 \\
egrand1 & cc by grandparents in yr 1 & 1 & 1 & 42 & 0.06 & 0.05 & 0.12 & 0.12 & 0.10 & 0.08 & 0.06 & 0.06 & 0.08 & 0.07 & 0.06 \\
eotrel1 & cc by oth rel in yr 1 & 1 & 1 & 42 & 0.03 & 0.02 & 0.02 & 0.07 & 0.10 & 0.02 & 0.01 & 0.02 & 0.02 & 0.01 & 0.01 \\
epnrel1 & paid cc by nonrelative in yr 1 & 1 & 1 & 40 & 0.02 & 0.01 & 0.01 & 0.05 & 0.00 & 0.01 & 0.01 & 0.00 & 0.02 & 0.00 & 0.00 \\
eunrel1 & unpaid cc by nonrelative in yr 1 & 1 & 1 & 40 & 0.01 & 0.00 & 0.01 & 0.00 & 0.00 & 0.01 & 0.00 & 0.01 & 0.01 & 0.01 & 0.01 \\
edaycar1 & cc by day care/preschool in year 1 & 1 & 1 & 39 & 0.04 & 0.03 & 0.04 & 0.09 & 0.05 & 0.04 & 0.04 & 0.02 & 0.04 & 0.02 & 0.04 \\
eschool1 & cc by kinderg/elementary in yr 1 & 1 & 1 & 40 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
enrel1 & any cc by nonrelative in yr 1 & 1 & 1 & 41 & 0.02 & 0.01 & 0.02 & 0.05 & 0.00 & 0.02 & 0.01 & 0.01 & 0.02 & 0.01 & 0.01 \\
evrel1 & ever used relative child care in year 1 & 1 & 1 & 44 & 0.15 & 0.12 & 0.19 & 0.21 & 0.19 & 0.17 & 0.11 & 0.13 & 0.16 & 0.13 & 0.11 \\
\end{longtable}
\end{landscape}
\section{Propensity score plots}
The following figures display the overlap of the sequential treatment propensity scores across treatment states in the empirical application by means of kernel density plots. Each figure is divided into four windows. The upper windows show the first and second period propensity scores $\hat{p}^{d_1}(X_0)$ and $\hat{p}^{d_2}(d_1,\underline{X}_1)$ under the treatment sequence. The bottom windows display the overlap for the corresponding first and second period propensity scores under the control sequence.
\begin{figure}[htbp]
\caption{Support for treatment sequences 33 vs.\ 22 with a trimming threshold of 0.01}
\end{figure}
\begin{figure}[htbp]
\caption{Support for treatment sequences 33 vs.\ 21 with a trimming threshold of 0.01}
\end{figure}
\begin{figure}[htbp]
\caption{Support for treatment sequences 33 vs.\ 11 with a trimming threshold of 0.01}
\end{figure}
\begin{figure}[htbp]
\caption{Support for treatment sequences 33 vs.\ 22 with a trimming threshold of 0.03}
\end{figure}
\begin{figure}[htbp]
\caption{Support for treatment sequences 33 vs.\ 21 with a trimming threshold of 0.03}
\end{figure}
\begin{figure}[htbp]
\caption{Support for treatment sequences 33 vs.\ 11 with a trimming threshold of 0.03}
\end{figure}