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Exploiting Gene-Environment Independence For Analysis Of Case-Control Studies: An Empirical Bayes Approach To Trade Off Between Bias And Efficiency , Bhramar Mukherjee

The University of Michigan Department of Biostatistics Working Paper Series

Standard prospective logistic regression analysis of case-control data often leads to very imprecise estimates of gene-environment interactions due to small numbers of cases or controls in cells of crossing genotype and exposure. In contrast, modern ``retrospective'' methods, including the celebrated ``case-only'' approach, can estimate the interaction parameters much more precisely, but they can be seriously biased when the underlying assumption of gene-environment independence is violated. In this article, we propose a novel approach to analyze case-control data that can relax the gene-environment independence assumption using an empirical Bayes (EB) framework. In the special case, involving a binary gene and a …