AN EMPIRICAL MODEL OF LEARNING UNDER AMBIGUITY: THE CASE OF CLINICAL TRIALS* AN EMPIRICAL MODEL OF LEARNING UNDER AMBIGUITY: THE CASE OF CLINICAL TRIALS.

This article presents a two-dimensional structural model of learning under ambiguity in the context of clinical trials. Clinical trials offer an ideal environment to study learning under ambiguity. The randomization process found in these studies leaves patients uncertain to their actual group assig...

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Bibliographic Details
Published in:International Economic Review Vol. 54; no. 2; pp. 549 - 574
Main Author: Fernandez, Jose M.
Format: Article
Published: Wiley-Blackwell May2013
Subjects:
Online Access:View this record in EBSCOhost
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      dt: May2013
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      pub: Wiley-Blackwell
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        10.1111/iere.12006
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        atl: AN EMPIRICAL MODEL OF LEARNING UNDER AMBIGUITY: THE CASE OF CLINICAL TRIALS* AN EMPIRICAL MODEL OF LEARNING UNDER AMBIGUITY: THE CASE OF CLINICAL TRIALS.
      aug:
        au: Fernandez, Jose M.
        affil: University of Louisville, U.S.A.
      su:
        Empirical research
        Economic models
        Clinical trials
        Drug side effects
        Structural frame models
        Treatment effectiveness
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        subj:
          Empirical research
          Economic models
          Clinical trials
          Drug side effects
          Research and Development in the Physical, Engineering, and Life Sciences (except Biotechnology)
          Structural frame models
          Treatment effectiveness
      ab: This article presents a two-dimensional structural model of learning under ambiguity in the context of clinical trials. Clinical trials offer an ideal environment to study learning under ambiguity. The randomization process found in these studies leaves patients uncertain to their actual group assignment. Therefore, patients cannot immediately attribute changes in health to the experimental drug. The article proposes the use of 'learning instrumental variables' to simultaneously update patients' beliefs of the treatment effect and group assignment. Patient learning is found to be faster when observable side effects are incorporated to account for the uncertainty in group assignment.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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