The heritability of negative life events was entirely accounted for in our Cholesky decomposition and genetic correlations in the correlated factors solution were significant for oppositionality, delinquency, physical aggression and depression.
We therefore transformed the Cholesky decompositions into the more easily interpretable correlated factors solution (Loehlin 1996) and report bivariate genetic correlations and factor loadings.
The correlated factor solution is the least restricted model allowing variables to correlate with one another via genetic, shared environment, and non-shared environment.
Relative to the saturated model, an ADE correlated factors solution had most negative BIC value (−157,928.84).
Lastly, even with the correlated factor solution, there are still some negative factor scoring coefficients.
So as to not give precedence to the latent variables underlying the first factor (here: parents' ratings), a correlated factor solution of the Cholesky model is presented.
The Cholesky decomposition, represented as a multivariate correlated factors solution (Fig. 1a), was used to examine the genetic and environmental relationship between mindfulness, depressive symptoms, and anxiety sensitivity.
We used a standard Cholesky decomposition, converted to the mathematically equivalent correlated factors solution, to estimate the degree of genetic and environmental overlap between our longitudinal measures.
Structural equation twin model fitting was used to estimate A, C, D, and E. A Cholesky decomposition, presented here as a mathematically equivalent correlated factors solution [ Loehlin, 1996], was fitted to data.
We further converted the initial Cholesky decomposition into a correlated factor solution, which provides two useful summary statistics of the relationship between any pair of variables: the correlation between latent components, and the proportion of the phenotypic correlation explained by each of the ACE components.
