title: Operating Characteristics of Statistical Methods for Detecting Gene-by-Measured Environment Interaction in the Presence of Gene-Environment Correlation under Violations of Distributional Assumptions.
abstract: Accurately identifying interactions between genetic vulnerabilities and environmental factors is of critical importance for genetic research on health and behavior. In the previous work of Van Hulle et al. (Behavior Genetics, Vol. 43, 2013, pp. 71-84), we explored the operating characteristics for a set of biometric (e.g., twin) models of Rathouz et al. (Behavior Genetics, Vol. 38, 2008, pp. 301-315), for testing gene-by-measured environment interaction (GxM) in the presence of gene-by-measured environment correlation (rGM) where data followed the assumed distributional structure. Here we explore the effects that violating distributional assumptions have on the operating characteristics of these same models even when structural model assumptions are correct. We simulated N = 2,000 replicates of n = 1,000 twin pairs under a number of conditions. Non-normality was imposed on either the putative moderator or on the ultimate outcome by ordinalizing or censoring the data. We examined the empirical Type I error rates and compared Bayesian information criterion (BIC) values. In general, non-normality in the putative moderator had little impact on the Type I error rates or BIC comparisons. In contrast, non-normality in the outcome was often mistaken for or masked GxM, especially when the outcome data were censored.
authors.affiliation: Waisman Center,University of Wisconsin-Madison,Madison,WI,USA.
authors.forename: Carol A
authors.initials: CA
authors.lastname: Van Hulle
authors.affiliation: Department of Biostatistics and Medical Informatics,University of Wisconsin School of Medicine and Public Health,Madison,WI,USA.
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Rathouz
mesh_terms: D000704:Analysis of Variance; D001499:Bayes Theorem; D003198:Computer Simulation; D059647:Gene-Environment Interaction; D006801:Humans; D016013:Likelihood Functions; D008957:Models, Genetic; D017711:Nonlinear Dynamics; D016011:Normal Distribution; D010641:Phenotype; D012984:Software; D016008:Statistical Distributions; D018433:Twin Studies as Topic / Q000706:statistics & numerical data*; D014429:Twins, Dizygotic / Q000235:genetics / Q000706:statistics & numerical data; D014430:Twins, Monozygotic / Q000235:genetics / Q000706:statistics & numerical data
keywords: rGE