Does structural equation modeling substitute for factor analysis, analysis of variance and path analysis?

It is well-known that structural equation modeling (SEM) can represent a variety 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 can more hardly be handled than a specifi cm odel developed for a particular situation given. In this paper, we shall clarify relative advantages between SEM and several traditional statistical models. Rather than comparioson in mathematical properties, we shall discuss how and when SEM outperforms corresponding traditional models in practical situations .A special attention is paid to statistical analysis of a scale score, a sum of indicator variables determined by factor analysis. In concrete, we shall study relative advantages between (i) exploratory factor analysis and confirmatory factor analysis models, (ii) correlational and regression analysis of scale scores and multiple indicator models, (iii) analysis of variance of scale scores and factor-mean models and (iv) multiple regression analysis and path analysis models.