Bayes and empirical Bayes methods for reduced rank regression models in matched case-control studies.

ABSTRACT: Matched case-control studies are popular designs used in epidemiology for assessing the effects of exposures on binary traits. Modern studies increasingly enjoy the ability to examine a large number of exposures in a comprehensive manner. However, several risk factors often tend to be related in a nontrivial way, undermining efforts to identify the risk factors using standard analytic methods due to inflated type-I errors and possible masking of effects. Epidemiologists often use data reduction techniques by grouping the prognostic factors using a thematic approach, with themes deriving from biological considerations. We propose shrinkage-type estimators based on Bayesian penalization methods to estimate the effects of the risk factors using these themes. The properties of the estimators a

SUBMITTER: Satagopan JM 

PROVIDER: S-EPMC4870158 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature