Generalizing Signaling Strategies in Multi-phase Trials

:::info Authors:

(1) Shih-Tang Su, University of Michigan, Ann Arbor ([email protected]);

(2) Vijay G. Subramanian, University of Michigan, Ann Arbor and ([email protected]);

(3) Grant Schoenebeck, University of Michigan, Ann Arbor ([email protected]).

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Table of Links

Abstract and 1. Introduction

2. Problem Formulation

2.1 Model of Binary-Outcome Experiments in Two-Phase Trials

3 Binary-outcome Experiments in Two-phase Trials and 3.1 Experiments with screenings

3.2 Assumptions and induced strategies

3.3 Constraints given by phase-II experiments

3.4 Persuasion ratio and the optimal signaling structure

3.5 Comparison with classical Bayesian persuasion strategies

4 Binary-outcome Experiments in Multi-phase trials and 4.1 Model of binary-outcome experiments in multi-phase trials

4.2 Determined versus sender-designed experiments

4.3 Multi-phase model and classical Bayesian persuasion and References

4.3 Multi-phase model and classical Bayesian persuasion

\ Note that the pruned tree will potentially be unbalanced.

\ Lemma 7. Given an N-phase trial M with binary-outcome experiments, if there exists a pruned N-phase trial model P run(M) such that the following two conditions hold, then the sender’s expected utility is given by an equivalent single-phase Bayesian persuasion model.

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1. For every non-trivial determined experiment, its sibling is either a trivial or a sender-designed experiment.

   \

2. There exists a least one sender-designed experiment in each (from root to leaf) experiment sequence of P run(M).

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:::info This paper is available on arxiv under CC 4.0 license.

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