期刊
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
卷 100, 期 470, 页码 591-601出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/016214504000001411
关键词
case-control studies; conditional inference; Dirichlet process; endometrial cancer; equine epidemiology; exponential family; low birth weight study; matching; Metropolis-Hastings; missing data; retrospective studies
This article considers Bayesian analysis of matched case-control problems when one of the covariates is partially missing. Within the likelihood context, the standard approach to this problem is to posit a fully parametric model among the controls for the partially missing covariate as a function of the covariates in the model and the variables making up the strata. Sometimes the strata effects are ignored at this stage. Our approach differs not only in that it is Bayesian, but, far more importantly, in the manner in which it treats the strata effects. We assume a Dirichlet process prior with a normal base measure for the stratum effects and estimate all of the parameters in a Bayesian framework. Three matched case-controt examples and a simulation study are considered to illustrate our methods and the computing scheme.
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