We provide a reparameterization of the traditional regression model that incorporates a G2 term and we demonstrate that the use of this expanded equation solves the problems that currently exist when a cross-product term is used to model a three-category genotype variable. This reparameterization allows for the accurate reproduction of interactions that may exist in the data, and removes the constraint that the slope differences must be the same between groups and always follow the order 0, 1, 2 and the requirement that per strata regression lines must cross at the same point. Accordingly, as in the case of a binary variable interaction (e.g., an X-linked locus in males), the significance of the interaction term is once again based entirely on the slope differences between genotypic groups without con-founding the test with information about the intercepts or mean differences between genotypic groups. This revised model allows for accurate characterization and visualization of any gene-environment interaction effects that may exist in the data. We note that alternatively it is possible to use dummy-coded variables; for a three-category genotype two dummy variables
