each externalizing disorder. Second, bivariate regression models, in which P3 and each TF component were entered into the model together (i.e. a model including P3 and TF component 1, a model including P3 and TF component 2, etc.), were used to determine the ability of each TF component to uniquely discriminate diagnostic group membership in the presence of P3 (i.e. account for significant variance above and beyond that accounted for by P3). The significance of each univariate model was tested using a Z-score, derived from the ratio of the probit regression coefficient for each independent variable to its standard error. A chi-square difference test (df=1) was used to test for a significant difference between corresponding univariate and bivariate models (e.g. univariate model with TF component 1 only vs. bivariate model with P3 and TF component 1 together). A significant difference indicated that the univariate model did not adequately fit the data compared to the bivariate model, thus indicating that the added variable was accounting for a significant amount of variance. If the difference was not significant, the fit of the univariate model was deemed adequate, and it was concluded that the added variable was not accounting for any additional variance.
