In an attempt to maintain consistency with previous findings (Prescott et al. 1999), we first verified that the effects of common environmental factors could be set to 0. Dropping C did not produce a significant increase in model misfit (Table 4, Model 2). We next tested the significance of genetic effects specific to AUD: this test asks whether the genetic correlation between these phenotypes is no different from unity versus whether there are genetic factors that load onto AUD but do not load onto AA/AD. Setting the AUD-specific genetic effects (dashed lines in Figure 1, plus sex-specific genetic influences not depicted in the figure) to 0 significantly reduced model fit (Table 4, Model 3). Thus, the genetic correlation between DSM-IV and DSM-5 diagnoses is slightly, but significantly, less than unity (Table 5). Examination of the confidence intervals suggests that the decrease in fit is driven by the female portion of the sample, particularly the sex-specific genetic contributions to female phenotypic variance. Because the E term encompasses measurement error, in order to allow for the possibility of AUD-specific error we did
