Open Access
September 2012 Combining Expert Opinions in Prior Elicitation
Isabelle Albert, Sophie Donnet, Chantal Guihenneuc-Jouyaux, Samantha Low-Choy, Kerrie Mengersen, Judith Rousseau
Bayesian Anal. 7(3): 503-532 (September 2012). DOI: 10.1214/12-BA717


We consider the problem of combining opinions from different experts in an explicitly model-based way to construct a valid subjective prior in a Bayesian statistical approach. We propose a generic approach by considering a hierarchical model accounting for various sources of variation as well as accounting for potential dependence between experts. We apply this approach to two problems. The first problem deals with a food risk assessment problem involving modelling dose-response for Listeria monocytogenes contamination of mice. Two hierarchical levels of variation are considered (between and within experts) with a complex mathematical situation due to the use of an indirect probit regression. The second concerns the time taken by PhD students to submit their thesis in a particular school. It illustrates a complex situation where three hierarchical levels of variation are modelled but with a simpler underlying probability distribution (log-Normal).


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Isabelle Albert. Sophie Donnet. Chantal Guihenneuc-Jouyaux. Samantha Low-Choy. Kerrie Mengersen. Judith Rousseau. "Combining Expert Opinions in Prior Elicitation." Bayesian Anal. 7 (3) 503 - 532, September 2012.


Published: September 2012
First available in Project Euclid: 28 August 2012

zbMATH: 1330.62106
MathSciNet: MR2981623
Digital Object Identifier: 10.1214/12-BA717

Keywords: Bayesian statistics , hierarchical model , random effects , risk assessment

Rights: Copyright © 2012 International Society for Bayesian Analysis

Vol.7 • No. 3 • September 2012
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