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Designing Persuasive Experiments

Karun Adusumilli, Abhi Vemulapati

arXiv 15 May 2026 · Econometrics

arXiv:2605.16703 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Incentives in experimental design are often misaligned: experimenters design and finance experiments to seek regulatory approval, while regulators seek to maximize social-welfare. We propose a framework to resolve this conflict, wherein regulators set a minimum welfare threshold, and experimenters optimize designs subject to this constraint. It requires no knowledge of experimenters' private preferences or costs and mitigates strategic Bayesian persuasion. Under normal priors, Neyman-allocation is always the optimal-sampling strategy, regardless of specific objectives. We also characterize the optimal stopping-rule. A numerical study calibrated to clinical-trial data shows sample-size reductions of over 48% relative to classical designs attaining the same social-welfare.

Citation extraction

40
references
104
in-text mentions
40
distinct cited
3
self-citations
14,844
main-text words

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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
1Adusumilli, Karun (2025) How to Sample and When to Stop Sampling: The Generalised Wald Problem and Minimax Policies self0.96510590%
2Adusumilli, Karun (2026) Continuous Time Asymptotic Representations for Adaptive Experiments self0.8947471%
3Tetenov, Aleksey (2016) An Economic Theory of Statistical Testing0.81142100%
4US Food and Drug Admin (2026) Use of Bayesian Methodology in Clinical Trials of Drug and Biological Products0.81142100%
5Liang, Annie and Mu, Xiaosheng and Syrgkanis, Vasilis (2022) Dynamically Aggregating Diverse Information0.76911545%
6van Zwet, Erik and Schwab, Simon and Senn, Stephen (2021) The Statistical Properties of RCTs and a Proposal for Shrinkage0.64441100%
7Bather, J. A. and Walker, A. M (1962) Bayes Procedures for Deciding the Sign of a Normal Mean0.64422100%
8Kenneth J. Arrow and David Blackwell and M.A. Girshick (1949) Bayes and Minimax Solutions of Sequential Decision Problems0.64422100%
9Hirano, Keisuke and Porter, Jack R (2025) Asymptotic Representations for Sequential Decisions, Adaptive Experiments, and Batched Bandits0.64422100%
10Gentzkow, Matthew and Kamenica, Emir (2014) Costly Persuasion0.64422100%

Showing the top 10 of 40 scored citations.