Comparisons across sexes included a sex-based invariance analysis as described by Hoyle and Smith [55] and Spillane et al. [56]. These involved adding, using a stepwise process, constraints for equal factor loadings across the sexes, then constraints for equal variance of exogenous variables, then for equality of correlations among indicators for latent variables, and finally constraints for equal path coefficients. Chi square was used to evaluate whether each constraint significantly decreased the model fit [52]. Also, to better understand sex differences in these models, the results for each sex were examined separately.
