many relatively infrequent symptoms biases results in the direction of detecting substantial epistatic and G × E effects. Indeed, in this simple case, the effects of G × E and epistasis are expected to be more significant than the main effects of genes and environment. A square-root transformation of the skewed symptom counts strengthens support for additive effects, but fails to remove the apparent contribution of epistasis and G × E. In large samples, such as those simulated, the effects of G × E are expected to be statistically significant. With the smaller samples currently employed in psychiatric genetic epidemiology, significance of non-additive effects is comparable with that of the main effects pointing to a serious bias towards Type I Errors for the detection of epistasis ot G × E even in transformed symptom counts.
