Learning, Private Information, and the Economic Evaluation of Randomized Experiments
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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- Gregory S. Crawford & Matthew Shum, 2005. "Uncertainty and Learning in Pharmaceutical Demand," Econometrica, Econometric Society, vol. 73(4), pages 1137-1173, 07.
- James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
- James Heckman & Neil Hohmann & Jeffrey Smith & Michael Khoo, 2000.
"Substitution and Dropout Bias in Social Experiments: A Study of an Influential Social Experiment,"
The Quarterly Journal of Economics,
Oxford University Press, vol. 115(2), pages 651-694.
- James Heckman & Neil Hohmann & Jeffrey Smith, 1998. "Substitution and Dropout Bias in Social Experiments: A Study of an Influential Social Experiment," UWO Department of Economics Working Papers 9819, University of Western Ontario, Department of Economics.
- Anup Malani, 2006. "Identifying Placebo Effects with Data from Clinical Trials," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 236-256, April. Full references (including those not matched with items on IDEAS)