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Parametric Bayesian analysis of case-control data with imprecise exposure measurements

✍ Scribed by Paul Gustafson; Nhu D Le; Marc Vallée

Publisher: Elsevier Science
Year: 2000
Tongue: English
Weight: 176 KB
Volume: 47
Category: Article
ISSN: 0167-7152
DOI: 10.1016/s0167-7152(99)00178-9

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✦ Synopsis

Case-control data with imprecise exposure measurements can be analyzed via Bayesian ÿtting of a retrospective discriminant analysis model. The parameters of interest are the regression coe cients in the prospective log-odds ratio for disease. Under a standard noninformative prior, the posterior means of these parameters are inÿnite. Posterior medians, however, perform reasonably relative to other estimators that adjust for covariate imprecision. The Bayesian inference can be implemented with direct posterior simulation, so the analysis is not complicated by convergence and dependence issues associated with Markov chain Monte Carlo methods.

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