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Optimal sequential treatment allocation

Anders Bredahl Kock, Martin Thyrsgaard

arXiv 28 May 2017 · Statistics — Machine Learning · 7 citations (OpenAlex)

arXiv:1705.09952 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In treatment allocation problems the individuals to be treated often arrive sequentially. We study a problem in which the policy maker is not only interested in the expected cumulative welfare but is also concerned about the uncertainty/risk of the treatment outcomes. At the outset, the total number of treatment assignments to be made may even be unknown. A sequential treatment policy which attains the minimax optimal regret is proposed. We also demonstrate that the expected number of suboptimal treatments only grows slowly in the number of treatments. Finally, we study a setting where outcomes are only observed with delay.

Citation extraction

34
references
43
in-text mentions
34
distinct cited
0
self-citations
13,692
main-text words

appendix boundary found by appendix_titled_section at “Appendix” · 60% of the source is main text. Read the extracted text to check this.

Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1V. Perchet and P. Rigollet (2013) The multi-armed bandit problem with covariates0.7375340%
2Toru Kitagawa and Aleksey Tetenov (2015) Who should be treated? empirical welfare maximization methods for treatment choice0.73732100%
3Sébastien Bubeck and Nicolo Cesa-Bianchi (2012) Regret analysis of stochastic and nonstochastic multi-armed bandit problems0.64422100%
4Charles F. Manski (2004) Statistical treatment rules for heterogenous populations0.51121100%
5Herbert Robbins (1952) Some aspects of the sequential design of experiments0.40511100%
6J. Stoye (2009) Minimax regret treatment choice with finite samples0.40511100%
7Susan Athey and Stefan Wager (2017) Efficient policy learning0.40511100%
8Anthony B Atkinson (1970) On the measurement of inequality0.40511100%
9Debopam Bhattacharya and Pascaline Dupas (2012) Inferring welfare maximizing treatment assignment under budget constraints0.40511100%
10Patrick Bolton and Christopher Harris (1999) Strategic experimentation0.40511100%

Showing the top 10 of 34 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Functional Sequential Treatment Allocation0.92843
2Functional Sequential Treatment Allocation with Covariates0.51121
3Treatment recommendation with distributional targets0.51121
4Optimal Dynamic Treatment Regimes and Partial Welfare Ordering0.40511
5Welfare Analysis via Marginal Treatment Effects0.40511
6Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints0.40511
7Identification and Inference for Welfare Gains without Unconfoundedness0.40511
8Asymptotic Representations for Sequential Decisions, Adaptive Experiments, and Batched Bandits0.40511