Fig. 2 |. The reflective latent variable model.

Reflective latent variable (common factor) model in which the unobserved psychobiological attribute (factor or latent construct; ξ), is conceptualized as explaining the variance/covariance in the measured variables (x_1,1–x_1,4) via their factor loadings (λx_1,1–λx_1,4), which are linear regression coefficients. The indicator error variances (also residual variances or uniquenesses; θε_1,1−θε_1,4) capture the variance in each measured variable not explained by the factor (that is, variance not shared with the other indicator variables).