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

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  • Fernandez, Jose

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.

Suggested Citation

  • Fernandez, Jose, 2008. "An Empirical Model of Learning under Ambiguity: The Case of Clinical Trials," MPRA Paper 8621, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:8621
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    Cited by:

    1. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    2. Mark Egan & Tomas Philipson, 2016. "Health Care Adherence and Personalized Medicine," Working Papers 2016-H01, Becker Friedman Institute for Research In Economics.
    3. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    4. Jürgen Maurer & Katherine M. Harris, 2016. "Learning to Trust Flu Shots: Quasi‐Experimental Evidence from the 2009 Swine Flu Pandemic," Health Economics, John Wiley & Sons, Ltd., vol. 25(9), pages 1148-1162, September.
    5. Maurer, J. & Harris, K.M., 2015. "Learning to trust flu shots: quasi-experimental evidence on the role of learning in influenza vaccination decisions from the 2009 influenza A/H1N1 (swine flu) pandemic," Health, Econometrics and Data Group (HEDG) Working Papers 15/19, HEDG, c/o Department of Economics, University of York.

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    More about this item

    Keywords

    clinical trials; learning; Bayesian; structural model; treatment effect;
    All these keywords.

    JEL classification:

    • 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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