BAYESIAN SEMIPARAMETRIC ANALYSIS FOR TWO-PHASE STUDIES OF GENE-ENVIRONMENT INTERACTION.

ABSTRACT: The two-phase sampling design is a cost-efficient way of collecting expensive covariate information on a judiciously selected sub-sample. It is natural to apply such a strategy for collecting genetic data in a sub-sample enriched for exposure to environmental factors for gene-environment interaction (G × E) analysis. In this paper, we consider two-phase studies of G × E interaction where phase I data are available on exposure, covariates and disease status. Stratified sampling is done to prioritize individuals for genotyping at phase II conditional on disease and exposure. We consider a Bayesian analysis based on the joint retrospective likelihood of phase I and phase II data. We address several important statistical issues: (i) we consider a model with multiple

SUBMITTER: Ahn J 

PROVIDER: S-EPMC3935248 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature