Fernandez, Jose (2008): An Empirical Model of Learning under Ambiguity: The Case of Clinical Trials.
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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.
Item Type: | MPRA Paper |
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Original Title: | An Empirical Model of Learning under Ambiguity: The Case of Clinical Trials |
Language: | English |
Keywords: | clinical trials, learning, Bayesian, structural model, treatment effect |
Subjects: | D - Microeconomics > D8 - Information, Knowledge, and Uncertainty C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C31 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions ; Social Interaction Models I - Health, Education, and Welfare > I1 - Health |
Item ID: | 8621 |
Depositing User: | Jose Fernandez |
Date Deposited: | 07 May 2008 04:52 |
Last Modified: | 28 Sep 2019 06:00 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/8621 |