Structural Equation Models

Abstract

In most of the multivariate linear models analyzed to this point, we formulated relationships between one observed independent set of variables and a set of random dependent variables where the covariance structure of the dependent set involved an unknown and unstructured covariance matrix Σ. Two exceptions to this paradigm included mixed models where Σ was formulated to have structure which contained components of variance and the exploratory factor analysis (EFA) model where Σ depended upon the unknown regression (pattern) coefficients which related unobserved (latent) factors to observed dependent variables.