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SOME COMMENTS ON MISSPECIFICATION OF PRIORS IN BAYESIAN MODELLING OF MEASUREMENT ERROR PROBLEMS

✍ Scribed by SYLVIA RICHARDSON; LAURENT LEBLOND

Publisher
John Wiley and Sons
Year
1997
Tongue
English
Weight
406 KB
Volume
16
Category
Article
ISSN
0277-6715

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✦ Synopsis

In this paper we discuss some aspects of misspecification of prior distributions in the context of Bayesian modelling of measurement error problems. A Bayesian approach to the treatment of common measurement error situations encountered in epidemiology has been recently proposed. Its implementation involves, first, the structural specification, through conditional independence relationships, of three submodelsa measurement model, an exposure model and a disease modeland secondly, the choice of functional forms for the distributions involved in the submodels. We present some results indicating how the estimation of the regression parameters of interest, which is carried out using Gibbs sampling, can be influenced by a misspecification of the parametric shape of the prior distribution of exposure.

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