Interpretation of a statistically significant GxE interaction is of particular interest. In the context of behavioural outcomes, two competing models exist for explaining gene-environment interplay. The diathesis stress model (Monroe & Simons, 1991) and differential susceptibly model (Belsky, 1997). Others have referred to these as fan-shaped vs cross-over interactions, respectively, due to their plotted appearance (Roisman et al., 2012). In the differential susceptibility model a particular genotype will perform significantly better under one environmental condition versus other genotypes and will also perform significantly worse than other genotype under an alternative environmental condition (a cross-over). In the diathesis-stress model, genotypes differ under only one environmental condition (a fan-shape). Frequently investigators plot interactions with the environment on the x-axis and phenotype on the y-axis, with separate lines per genotype, and draw conclusions based on visual inspection. However, formal statistical procedures exist for determining regions of significance, values of the environmental exposure under which genotypes differ significantly on phenotypic measures. In the instance of discrete environmental measures, this approach is simple since it involves comparing genotypes on phenotypic measure at each level of
