Fourth, our models are quite conservative in that they adjust for any possibility of population stratification and gene-environment correlation. It is possible that one or both of these factors account for our inability to detect associations at genome-wide significance levels. To examine this possibility, we reestimated the same GWGEI models presented in Fig. 2 without the adjustment for parental mating type (population stratification) or the interaction between parental mating type and college degree status (gene-environment correlation). These results are summarized in two diagrams in Fig. 5. The left panel plots the bivariate association between the p value (–log10) from the fully adjusted GWGEI model (those from Fig. 2) and the p values from the GWGEI models without controls for population stratification or gene-environment correlation. If these controls did not affect the p values for the two models, we would expect to see a clear linear association between the values: this is clearly not the case. In fact, the bivariate correlation between the two logged p values is only .30. The right panel is the QQ plot for the unadjusted GWGEI
