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 proposed model fits the observed data. SEM allows researchers to test hypotheses about relationships among multiple variables simultaneously. In SEM, researchers specify a model that includes both observed variables and latent variables, which are not directly measured. The technique provides estimates of the strength and direction of these relationships, helping to identify direct and indirect effects. This makes SEM a powerful tool for understanding intricate systems in fields like psychology, sociology, and economics.