Bayes and empirical Bayes methods for reduced rank regression models in matched case-control studies Academic Article uri icon

Overview

MeSH Major

  • Case-Control Studies
  • Models, Statistical

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 are examined using extensive simulations. The methodology is illustrated using data from a matched case-control study of polychlorinated biphenyls in relation to the etiology of non-Hodgkin's lymphoma.

publication date

  • June 2016

Research

keywords

  • Academic Article

Identity

Language

  • eng

PubMed Central ID

  • PMC4870158

Digital Object Identifier (DOI)

  • 10.1111/biom.12444

PubMed ID

  • 26575519

Additional Document Info

start page

  • 584

end page

  • 95

volume

  • 72

number

  • 2