title: Detecting specific genotype by environment interactions using marginal maximum likelihood estimation in the classical twin design.
abstract: Considerable effort has been devoted to the analysis of genotype by environment (G × E) interactions in various phenotypic domains, such as cognitive abilities and personality. In many studies, environmental variables were observed (measured) variables. In case of an unmeasured environment, van der Sluis et al. (2006) proposed to study heteroscedasticity in the factor model using only MZ twin data. This method is closely related to the Jinks and Fulker (1970) test for G × E, but slightly more powerful. In this paper, we identify four challenges to the investigation of G × E in general, and specifically to the heteroscedasticity approaches of Jinks and Fulker and van der Sluis et al. We propose extensions of these approaches purported to solve these problems. These extensions comprise: (1) including DZ twin data, (2) modeling both A × E and A × C interactions; and (3) extending the univariate approach to a multivariate approach. By means of simulations, we study the power of the univariate method to detect the different G × E interactions in varying situations. In addition, we study how well we could distinguish between A × E, A × C, and C × E. We apply a multivariate version of the extended model to an empirical data set on cognitive abilities.
authors.affiliation: Department of Psychology, University of Amsterdam, Weesperplein 4, Amsterdam, The Netherlands. D.Molenaar@uva.nl
authors.forename: Dylan
authors.initials: D
authors.lastname: Molenaar
authors.forename: Sophie
authors.initials: S
authors.lastname: van der Sluis
authors.forename: Dorret I
authors.initials: DI
authors.lastname: Boomsma
authors.forename: Conor V
authors.initials: CV
authors.lastname: Dolan
mesh_terms: D000293:Adolescent; D001741:Black or African American; D000465:Algorithms; D003198:Computer Simulation; D016001:Confidence Intervals; D005260:Female; D059647:Gene-Environment Interaction; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D015233:Models, Statistical; D015999:Multivariate Analysis; D017711:Nonlinear Dynamics; D010641:Phenotype; D012107:Research Design; D018433:Twin Studies as Topic / Q000706:statistics & numerical data*