An Empirical Model of Learning under Ambiguity: The Case of Clinical Trials
AbstractIn this paper, I present an empirical model of learning under ambiguity in the context of clinical trials. Patients are concern with learning the treatment effect of the experimental drug, but face the ambiguity of random group assignment. A two dimensional Bayesian model of learning is proposed to capture patients�beliefs on the treatment effect and group assignment. These beliefs are then used to predict patient attrition in clinical trials. Patient learning is demonstrated to be slower when taking into account group ambiguity. In addition, the model corrects for attrition bias in the estimated treatment effect.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 8621.
Date of creation: 03 Apr 2008
Date of revision:
clinical trials; learning; Bayesian; structural model; treatment effect;
Other versions of this item:
- Jose M. Fernandez, 2013. "An Empirical Model Of Learning Under Ambiguity: The Case Of Clinical Trials," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(2), pages 549-573, 05.
- D8 - Microeconomics - - Information, Knowledge, and Uncertainty
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- I1 - Health, Education, and Welfare - - Health
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