Applications of Structural Equation Modelling in Social Sciences Research

Abstract

Structural Equation Modeling (SEM) has emerged as a powerful analytical tool in social sciences research, offering a robust approach to examining complex relationships among observed and latent variables. Unlike traditional regression models, SEM enables researchers to simultaneously analyze multiple dependent and independent variables, account for measurement errors, and evaluate theoretical models comprehensively. This paper provides an overview of SEM applications in social sciences, emphasizing its advantages, key methodological steps, and limitations.