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Learning, Private Information, and the Economic Evaluation of Randomized Experiments

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Author Info
Tat Y. Chan
Barton H. Hamilton
Abstract

Many randomized experiments are plagued by attrition, even among subjects receiving more effective treatments. We estimate the subject's utility associated with the receipt of treatment, as revealed by dropout behavior, to evaluate treatment effects. Utility is a function of both "publicly observed" outcomes and side effects privately observed by the subject. We analyze an influential AIDS clinical trial, ACTG 175, and show that for many subjects, AZT yields the highest level of utility despite having the smallest impact on the publicly observed outcome because of mild side effects. Moreover, although subjects enter the experiment uncertain of treatment effectiveness (and often the treatment received), the learning process implies that early dropout in ACTG 175 is primarily driven by side effects, whereas later attrition reflects declining treatment effectiveness.

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Article provided by University of Chicago Press in its journal Journal of Political Economy.

Volume (Year): 114 (2006)
Issue (Month): 6 (December)
Pages: 997-1040
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Handle: RePEc:ucp:jpolec:v:114:y:2006:i:6:p:997-1040

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  1. Mark Duggan & William Evans, 2008. "Estimating the Impact of Medical Innovation: A Case Study of HIV Antiretroviral Treatments," Forum for Health Economics & Policy, Berkeley Electronic Press, vol. 11(2), pages 1102-1102. [Downloadable!] (restricted)
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  2. van den Berg, Gerard J, 2007. "An Economic Analysis of Exclusion Restrictions for Instrumental Variable Estimation," CEPR Discussion Papers 6157, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  3. Fernandez, Jose, 2008. "An Empirical Model of Learning under Ambiguity: The Case of Clinical Trials," MPRA Paper 8621, University Library of Munich, Germany. [Downloadable!]
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