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

Jose Fernandez

MPRA Paper from University Library of Munich, Germany

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: clinical trials; learning; Bayesian; structural model; treatment effect (search for similar items in EconPapers)
JEL-codes: D8 C31 I1 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-hea
Date: 2008-04-03
View list of references

Downloads: (external link)
http://mpra.ub.uni-muenchen.de/8621/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany
Address: Schackstr. 4, D-80539 Munich, Germany
Contact information at EDIRC.
Series data maintained by Ekkehart Schlicht ().