PubMed · 16389918
On the multivariate probit model for exchangeable binary data with covariates.
Abstract
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.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Catalina Stefanescu, Bruce W Turnbull. 2005. On the multivariate probit model for exchangeable binary data with covariates.. https://doi.org/10.1002/bimj.200410101
Cite the original work for its findings. Save a collection to share your selection of sources.