Table 2 presents estimated correlations among variables in the cascade analysis, including the latent constructs for externalizing, internalizing, and social competence, and the observed CAD symptoms variables. Figure 1 depicts the evaluated nested models progressing from Models 1 to 6 by gradually freeing parameters, based on theory and comparing nested models. In Table 3, the paths freed in each of the successive nested models are indicated. Relative fit was evaluated with a scaled chi-square difference test for nested models (Satorra, 2000). Each of the more parsimonious models was compared with the next most complex model (see Table 4). The c coefficient in Table 4 refers to a scaling constant used in chi-square difference tests (see Satorra, 2000). Significant chi-square difference tests were used to assess for relative fit between more to less parsimonious nested models. The AIC, BIC, and chi-square difference tests confirm statistically significant incremental fit from Model 1 up to Model 5, whereas Model 6 shows no statistically enhanced fit. In the current cascade analysis within-time covariation could not be controlled at Wave 1 due to the common
