Structural Equation Modeling and Its Application in Psychological Studies: A Review Study

Structural Equation Modeling (SEM) is a very general statistical modeling technique, which is widely used in the behavioral sciences. It can be viewed as a combination of path analysis, regression and factor analysis. One of the prominent features of this method is the ability to compute direct, indirect and total effects, as well as latent variable modeling.

This systematic review study done on published original article in Iranian search database (Iranmedex, SID, Magiran) and international search database (Google Scholar, ISI, Scopus, Science Direct ، Pubmed) during year 1973 until 2018. In this study searched done with key words like " Correlation", " Path Analysis", " Factor Analysis: Confirmatory And Explanatory", " Structural Equation Modeling: SEM", " Latent variable", " Formative Model", " Reflective Model", "Multiple Indicators Multiple Causes: MIMIC", " Direct Effect", " Indirect Effect" and " Total Effect" and related Persian synonyms.

The review of articles contain structural equation modeling shows the new study areas like formative versus reflective structural models, Multiple Indicators Multiple Causes: MIMIC model, variance versus covariance model, structural models with non-normal response and use item response model for analyzing latent variables.

Considering advance growth in structural modeling, behavioral researchers can be more response to more complicated research questions