arXiv 25 Jul 2024 · Econometrics
arXiv:2407.18206 · PDF · DOI · OpenAlex · Extracted main text
We use the exact finite sample likelihood and statistical decision theory to answer questions of “why?” and “what should you have done?” using data from randomized experiments and a utility function that prioritizes safety over efficacy. We propose a finite sample Bayesian decision rule and a finite sample maximum likelihood decision rule. We show that in finite samples from 2 to 50, it is possible for these rules to achieve better performance according to established maximin and maximum regret criteria than a rule based on the Boole-Frechet-Hoeffding bounds. We also propose a finite sample maximum likelihood criterion. We apply our rules and criterion to an actual clinical trial that yielded a promising estimate of efficacy, and our results point to safety as a reason for why results were mixed in subsequent trials.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Manski, C. F (2004) Statistical treatment rules for heterogeneous populations | 0.928 | 4 | 3 | 100% |
| 2 | Ben-Michael, E., K. Imai, and Z. Jiang (2024) Policy learning with asymmetric counterfactual utilities | 0.811 | 4 | 2 | 100% |
| 3 | Stoye, J (2009) Minimax regret treatment choice with finite samples | 0.644 | 2 | 2 | 100% |
| 4 | Zabet, M. H., M. Mohammadi, M. Ramezani, and H. Khalili (2016) Effect of high-dose ascorbic acid on vasopressor's requirement in septic shock | 0.644 | 2 | 2 | 100% |
| 5 | Tian, J. and J. Pearl (2000) Probabilities of causation: Bounds and identification | 0.511 | 2 | 1 | 100% |
| 6 | Balke, A. and J. Pearl (1997) Bounds on treatment effects from studies with imperfect compliance | 0.405 | 1 | 1 | 100% |
| 7 | Boole, G (1854) Of statistical conditions | 0.405 | 1 | 1 | 100% |
| 8 | Canner, P. L (1970) Selecting one of two treatments when the responses are dichotomous | 0.405 | 1 | 1 | 100% |
| 9 | Copas, J. B (1973) Randomization models for the matched and unmatched 2 x 2 tables | 0.405 | 1 | 1 | 100% |
| 10 | Cox, D. R (1958) Planning of Experiments | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 50 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Counting Defiers: A Design-Based Model of an Experiment Can Reveal Evidence Beyond the Average Effect | 0.405 | 1 | 1 |
| 2 | 3emHippocratic Utility | 0.405 | 1 | 1 |