The primary reason that power to detect interactions tends to be low is that the variance of the product term tends to be low in nonexperimental studies (8). Power to detect the effect of any predictor, including a product term, increases as a function of the variance of that predictor. The variance of product (here, cG×E) terms is maximized when subjects are selected from the joint extremes (high G–high E, low G–high E, high G–low E, and low G–low E) of the two first-order predictors, but such jointly extreme observations tend to be rare in nonexperimental studies (8). This issue is particularly relevant to cG×E studies, as it is generally not possible to sample from the genotypic extremes (e.g., equal numbers of the two homozygotes). Thus, power in cG×E studies will be maximized whenever variance in the two first-order predictors is maximized, that is, when the minor allele frequencies are high (e.g., 0.50 for biallelic loci) and when equal numbers of subjects are exposed to the extremes of the environmental moderator (25). Additional factors such as ascertainment strategy (29), study
