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On the Multivariate Probit Model for Exchangeable Binary Data with Covariates

✍ Scribed by Catalina Stefanescu; Bruce W. Turnbull

Publisher: John Wiley and Sons
Year: 2005
Tongue: English
Weight: 153 KB
Volume: 47
Category: Article
ISSN: 0323-3847
DOI: 10.1002/bimj.200410101

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✦ Synopsis

This paper considers the use of a multivariate binomial probit model for the analysis of correlated exchangeable binary data. The model can naturally accommodate both cluster and individual level covariates, while keeping a fairly flexible intracluster association structure. We discuss Bayesian estimation when a sample of independent clusters of varying sizes are available, and show how Gibbs sampling may be used to derive the posterior densities of parameters. The methodology is illustrated with two examples: the first involves epidemiological data from a study of familial disease aggregation; the second uses teratological data from a developmental toxicity application.

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