Combining expert opinions in prior elicitation

Abstract : 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. Our main research findings are to propose a generic approach by considering a hierarchical model accounting for various sources of variation as well as accouting for potential dependence between esperts. We apply this approach to two problems. The first problem deals with a food risk assessment problem involving modelling dose-response for {\em 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).
Type de document :
Article dans une revue
Bayesian Analysis, International Society for Bayesian Analysis, 2012, 7 (3), pp.541-546
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-00703156
Contributeur : Sophie Donnet <>
Soumis le : vendredi 1 juin 2012 - 07:13:21
Dernière modification le : vendredi 17 février 2017 - 14:29:34

Identifiants

  • HAL Id : hal-00703156, version 1

Collections

Citation

Sophie Donnet, Judith Rousseau, Chantal Guihenneuc-Jouyaux, Kerrie L. Mengersen, Samantha Low Choy, et al.. Combining expert opinions in prior elicitation. Bayesian Analysis, International Society for Bayesian Analysis, 2012, 7 (3), pp.541-546. <hal-00703156>

Partager

Métriques

Consultations de la notice

263