Does Structural Equation Modeling Outperform Traditional Factor Analysis, Analysis of Variance and Path Analysis ?

Abstract

It is well-known that structural equation modeling (SEM) can represent a vari-ety of traditional multivariate statistical models. This fact does not necessarily mean that SEM should be used for the traditional models. It is often said that a general model is more difficult to handle than a specific model developed for a given situation. In this paper, we shall clarify relative advantages between SEM and several traditional statistical models. Rather than comparison in mathematical properties, we shall discuss how and when SEM outperforms corresponding traditional models in practical situations. Special attention is paid to statistical analysis of a scale score, the sum of indicator variables de-termined by factor analysis. In particular, we shall study relative advantages between (i) confirmatory factor analysis and exploratory factor analysis, (ii) multiple indicator analysis and correlational and regression analysis of scale scores, (iii) analysis of factor means and analysis of variance of scale scores, and (iv) path analysis and multiple regression analysis.