“…There, he proposed an important extension of the classic bivariate biometric model to allow testing interactions between a measured environment and each of the variance components (A, C, or E), while accounting for A-, C-, or E-by-measured environment correlations arising from the influence of genes (A) and environmental factors (C and E) common to both the phenotype and the measured environment. Since the publication of Purcell’s article, researchers have relied on his model to test gene-by-environment interactions for a wide range of phenotypes, including perceived control and physical health (Johnson & Krueger, 2005), family income and intelligence scores (Turkheimer, Haley, Waldron, D’Onofrio, & Gottesman, 2003), prenatal complications and asthma (van Beijsterveldt & Boomsma, 2008), protein intake and body composition (Silventoinen et al, 2009), marital quality and anxiety (South & Krueger, 2008), and others (Johnson, McCue, & Iacono, 2009; Lau & Eley, 2008). Whereas interactions between candidate moderators and additive genetic influences (A) were usually the focus of these studies, researchers typically tested the potentially important interactions between the candidate moderator and shared (C) and unshared (E) environmental influences as well.…”