Maximum likelihood genetic factor scores were estimated by computing the conditional likelihood of the twin pairs’ item responses, weighted by the joint likelihood of the factor score estimates. This is an application of Bayes’ theorem, in which the joint likelihood p(F,R), of the factor scores F and the item responses R, is evaluated as p(R|F)p(F). This factor score model was iteratively fitted, separately for each of the five different zygosity/sex groups, to each twin pair’s raw data to estimate genetic factor scores for each individual. To validate the genetic factors found in our best-fit twin model, we used these genetic factor scores to predict a representative group of variables unrelated to the DSM AD criteria. These measures included: one representative internalizing disorder and two representative externalizing psychiatric disorders known to be comorbid with AD;30–33 other critical clinical and historical features of alcohol use and problems and years of education (as an index of social class), which is known to be associated with AD.34 To determine if the genetic factor scores differed from each other in their prediction of the external
