Considering the raw and transformed results across the three moderators as a set, the question of why some moderators are more susceptible to transformation than others still remains. We tested if there were a differential number of bivariate outliers across each moderator and the alcohol use variable and found the number of bivariate outliers to be consistent across the moderators with both the raw and transformed alcohol use variable. Therefore the difference in susceptibility to transformation between environmental moderators is unlikely due to the bivariate distributions of these moderators. Instead, this difference could be in part due to the lack of an absolute metric for the environment. Latent GxE effects capture changes in heritability across different levels of the environment. And, like all heritability estimates, these estimates are sample specific (Verhulst et al., 2015). Therefore, GxE findings have the potential to vary both across difference studies and when the distribution of the outcome variable changes as the result of a non-linear transformation. An additional related complication is that, just like the complex traits of interest in GxE studies (including alcohol
