期刊名称：Brazilian Journal of Probability and Statistics
印刷版ISSN：0103-0752
出版年度：2000
卷号：14
期号：1
页码：87-111
出版社：Brazilian Statistical Association
摘要：Generalized linear models with scale mixture of multivariate normal (SMMVN) link functions are considered to model correlated ordinal response data. A unified Bayesian approach, which includes prior elicitation and model comparison, is proposed. In order to incorporate available prior information, we propose a class of informative prior distributions on model parameters. The propriety of the proposed informative prior is also examined in detail. Due to the complexity of SMMVN models, Markov chain Monte Carlo sampling is used to carry out all posterior computations. Finally, a real data example from prostate cancer studies is used to illustrate the proposed methodologies.
关键词：Bayesian computation; hierarchical model; latent variables;Markov chain Monte Carlo; multivariate generalized linear models; scale mixture;of multivariate normal links
