inclusion of covariate interaction terms in a model tested on the full dataset is a much more statistically powerful approach for controlling potential confounders than is splitting the data by covariates and testing the G×E term in each subset of the data. Finally, investigators should be assuaged by the fact that if covariate interaction terms have no true relationship with the G×E term, the G×E interaction estimate typically changes very little, and is as likely to be strengthened as weakened by proper inclusion of covariate interaction terms.
