Structural Equation Modeling in the Communication Sciences, 1995?2000

This study summarizes the use of this technique from 1995–2000 in 37 communication-based academic journals and identifies and critically assess 3 unique methods for testing structural relationships via SEM in terms of the specification, estimation, and evaluation of their respective structural equation models.

Abstract

Structural equation modeling (SEM) is a viable multivariate tool used by communication researchers for the past quarter century. Building off Cappella (1975) as well as McPhee and Babrow (1987), this study summarizes the use of this technique from 1995–2000 in 37 communication-based academic journals. We identify and critically assess 3 unique methods for testing structural relationships via SEM in terms of the specification, estimation, and evaluation of their respective structural equation models. We provide general guidelines for the use of SEM and make recommendations concerning latent variable models, sample size, reporting parameter estimates, model fit statistics, cross-sectional data, univariate normality, cross-validation, nonrecursive modeling, and the decomposition of effects (direct, indirect, and total).