The role of environmental heterogeneity in meta-analysis of gene-environment interactions with quantitative traits.

ABSTRACT: With challenges in data harmonization and environmental heterogeneity across various data sources, meta-analysis of gene-environment interaction studies can often involve subtle statistical issues. In this paper, we study the effect of environmental covariate heterogeneity (within and between cohorts) on two approaches for fixed-effect meta-analysis: the standard inverse-variance weighted meta-analysis and a meta-regression approach. Akin to the results in Simmonds and Higgins (), we obtain analytic efficiency results for both methods under certain assumptions. The relative efficiency of the two methods depends on the ratio of within versus between cohort variability of the environmental covariate. We propose to use an adaptively weighted estimator (AWE), between meta-analysis and meta-reg

SUBMITTER: Li S 

PROVIDER: S-EPMC4108593 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature