Structural Equation Modeling (SEM) is a statistical technique used to analyze complex relationships between variables. It combines elements of factor analysis and regression analysis to assess how well a theoretical model fits observed data. SEM allows researchers to test hypotheses about relationships among multiple variables simultaneously. In SEM, researchers specify a model that represents their theoretical understanding of the relationships among variables. This model includes both observed variables, which can be measured directly, and latent variables, which are inferred from the observed data. By estimating the strength and direction of these relationships, SEM helps in understanding the underlying structure of data.