In Figure 2A, we provide power estimates for cG×Es given three different effect sizes and plot them above a histogram of actual sample sizes from the first decade of cG×E studies (Figure 2B). Power estimates were derived from 10,000 Monte Carlo simulations with alpha set to 0.05. We assumed that no error occurred in any of the measures, and that the environmental and genetic variables accounted for 20% and 0.5% of the variance in the outcome variable, respectively. These are favorable values for the detection of G×E effects because increasing variance accounted for by the first-order terms increases power to detect an interaction term in linear regression.
