An Empirical Model of Learning Under Ambiguity: The Case of Clinical Trials

51 Pages Posted: 7 Nov 2007 Last revised: 6 May 2008

Date Written: April 18, 2008

Abstract

In 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.

Keywords: HIV, AIDS, Topamax, Learning, Bayesian, Clinical Trials

JEL Classification: D83, C5, C6, C91, C92, I1

Suggested Citation

Fernandez, Jose M., An Empirical Model of Learning Under Ambiguity: The Case of Clinical Trials (April 18, 2008). Available at SSRN: https://ssrn.com/abstract=1025765 or http://dx.doi.org/10.2139/ssrn.1025765

Jose M. Fernandez (Contact Author)

University of Louisville ( email )

College of Business
University of Louisville
Louisville, KY 40292
United States
5028524861 (Phone)

HOME PAGE: http://louisville.edu/faculty/jmfern02

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