genetic dominance, with 0 indicating 0 copies of the risk allele and 1 indicating one or two copies of the risk allele. Often, however, we do not know the true functional model associated with a given marker of interest. Accordingly, a common practice is to conduct initial tests assuming an additive genetic model, in which the gene is coded 0, 1, 2 to indicate the number of copies of a particular reference allele carried by an individual. We demonstrate that modeling gene-environment interaction (G × E) by way of a cross-product term frequently yields misleading results that can generate erroneous conclusions about the presence and magnitude of interaction effects when genotype is coded 0, 1, 2. This result has potentially important implications for the interpretation of gene-environment interaction effects derived using this method, including many of those in previously published articles. In this paper, we illustrate the problem and provide an alternative parameterization which can be used to estimate regression lines within each genotypic group that more accurately capture the nature of the interaction. Although the same problem exists when the dependent variable is dichotomous, we will explain our methods using continuous linear regression.
