Operating characteristics of alternative statistical methods for detecting gene-by-measured environment interaction in the presence of gene-environment correlation in twin and sibling studies.

ABSTRACT: It is likely that all complex behaviors and diseases result from interactions between genetic vulnerabilities and environmental factors. Accurately identifying such gene-environment interactions is of critical importance for genetic research on health and behavior. In a previous article we proposed a set of models for testing alternative relationships between a phenotype (P) and a putative moderator (M) in twin studies. These include the traditional bivariate Cholesky model, an extension of that model that allows for interactions between M and the underling influences on P, and a model in which M has a non-linear main effect on P. Here we use simulations to evaluate the type I error rates, power, and performance of the Bayesian Information Criterion under a variety of data generating mecha

SUBMITTER: Van Hulle CA 

PROVIDER: S-EPMC3552083 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature