In the discovery setting, focus is often on identifying novel genetic loci associated with disease. For GEWIS approaches, there is typically not a priori information as to whether multiplicative or additive models are most appropriate. When environmental factors and genetic loci only have modest effects on disease risk, there will not be large differences between additive and multiplicative tests [Weinberg 2012b]. However, similarity between the models breaks down when one of the main effects is large, or the environmental exposure is continuous. In general, Think Tank participants were supportive of considering approaches that were less dependent on the choice of additive or multiplicative parameterizations in the discovery setting. Joint tests consider the hypothesis that a genetic factor is associated with risk of disease in any exposure subgroup, and test the main effect of the genetic factor and the GxE interaction simultaneously in a 2-degree of freedom test [Kraft, et al. 2007]. Alternative versions of this test have been proposed [Dai, et al. 2012b] and the GxE independence assumption can be incorporated into joint tests to improve power using MLE [Chatterjee
