Fundamentals of Structural Equation Modeling (SEM)

Abstract

The use of Structural Equation Modeling (SEM) in the humanities and social sciences has become an essential and indispensable approach that must be adopted in future field research, particularly in psychology. This shift comes after moving beyond the traditional reliance on complex and multiple hypotheses that demand considerable time and effort from researchers, while often failing to fully capture or control all variables influencing the phenomenon under study. In contrast, structural modeling enables the simultaneous examination of a large and complex set of interrelated relationships, while also accounting—at least partially—for measurement errors in the observed variables.
Given the importance of this modern statistical approach, the aim of this article is to present clear analytical concepts regarding Structural Equation Modeling (SEM), its objectives, key advantages, fundamental principles, and the most commonly used model types. This will be supported by practical examples and applied research models to enhance understanding.