reach erroneous conclusions about the role of environmental factors. By creatively using these data to account for genetic factors that predict the independent and dependent variables, demographers can rule out alternative explanations. Lee and colleagues (2012) extended the GCTA model to include an estimate of genetic correlation using a bivariate approach. At a minimum, if genome-wide data are available, researchers can easily demonstrate absence of genetic correlation, which in turn reduces the likelihood of genetic confounding resulting from gene-environment correlation.
