Semiparametric Bayesian analysis of matched case-control studies with missing exposure Academic Article

abstract

• 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-control examples and a simulation study are considered to illustrate our methods and the computing scheme. 2005 American Statistical Association.

authors

• Carroll, Raymond
• Mallick, Bani
• Sinha, Samiran

published proceedings

• JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

author list (cited authors)

• Sinha, S., Mukherjee, B., Ghosh, M., Mallick, B. K., & Carroll, R. J.

citation count

• 16

complete list of authors

• Sinha, S||Mukherjee, B||Ghosh, M||Mallick, BK||Carroll, RJ

publication date

• June 2005

publisher

• Taylor & Francis  Publisher

published in

• JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION  Journal

keywords

• Case-Control Studies
• Conditional Inference
• Dirichlet Process
• Endometrial Cancer
• Equine Epidemiology
• Exponential Family
• Low Birth Weight Study
• Matching
• Metropolis-hastings
• Missing Data
• Retrospective Studies

Digital Object Identifier (DOI)

• 10.1198/016214504000001411

start page

• 591

end page

• 601

volume

• 100

issue

• 470

URL

• http%3A%2F%2Fdx.doi.org%2F10.1198%2F016214504000001411