Introducing the Latent Congruence Model for Improving the Assessment of Similarity, Agreement, and Fit in Organizational Research

Abstract

A structural equation modeling—based latent congruence model (LCM) is developed for studying congruence in organizational research. Numerical examples are used to demonstrate that the LCM offers many advantages over the current approaches (difference scores, profile similarity indices, and polynomial regression) to studying congruence. The LCM can (a) control for measurement errors by specifying the congruence of latent variables, (b) examine measurement equivalence across the component measures, (c) examine the antecedents and consequences of both the mean (absolute level) and difference (congruence) of two component measures simultaneously, (d) study both congruence and components by decomposing the congruence measures into component measures, and (e) examine complex congruence models that include multiple congruence measures as antecedents and/or consequences.