Moderation models were fit to test whether the variance components differed as a function of each of the neighborhood variables. Figure 1 shows a classic twin model (for only 1 twin in the pair) that has been modified to include a moderation component (Purcell, 2002). The standard paths a, c, and e, indicating the magnitude of effect of additive genetic influences, common environmental influences, and unique environmental influences, now each include a β term, which indicates the significance of a potential moderator variable M on each of these genetic and environmental influences. The value of M changes from subject to subject, taking on the value of the measured variable for that subject (i.e., the socioregional variables in our models). In the moderation model, the additive genetic value is a linear function of the moderator M, represented by the equation a + βXM, where βX is an unknown parameter to be estimated from the data, representing the magnitude of the moderating effect. If βX is significantly different from zero, there is evidence for a moderating effect. A similar logic follows for
