To understand how A, C, and E factors influence the co-variance between all trait dimensions, we compared the correlated factor model (which examines correlations between each pair of dimensions) to the common and independent pathway models (which consider the correlations between all dimensions simultaneously)30. In the common pathway model, the co-variance of the OC trait dimensions is accounted for by a single latent phenotype influenced by shared additive genetic (Ac), common environment (Cc), and unique environment (Ec) factors. The model estimates dimension-specific genetic (As), common environment (Cs), and unique environment factors (Es). The independent pathway model accounts for co-variance of the dimensions by estimating Ac, Cc, and Ec factors that directly influence each dimension (i.e., not through a latent phenotype) and dimension-specific variance is accounted by estimating As, Cs, and Es factors for each dimension. The best fitting model was selected using the AIC.
