Multivariate analyses of the influence of GABRA2 genotype and social factors on alcohol dependence were modeled with random-effects logistic regression models (Fitzmaurice et al. 2004; Rabe-Hesketh and Skrondal 2008) estimated with the xtlogit command in Stata (StataCorp 2011). Examining GxE effects using regression-based approaches have a number of advantages, including the ability to control for potential confounding variables that are correlated with both genotype and alcohol dependence, and the capacity to test moderation models (Waldman et al. 1999). Random effects models were used because they adjust for the lack of independence among observations resulting from having multiple individuals from the same family. These models reflected individuals (level-1) nested in families (level-2), and contained family-level (i.e. cluster-specific) random intercepts (Rabe-Hesketh and Skrondal 2008).
