: These are "hidden" or abstract constructs that cannot be observed directly, such as intelligence, job satisfaction, or self-esteem.
Structural Equation Modeling (SEM) with latent variables is a powerful multivariate statistical technique used to test complex relationships between observed data and underlying, unobservable constructs. By combining factor analysis and path analysis, SEM allows researchers to account for measurement error while simultaneously testing multiple causal pathways. 1. Conceptual Framework: Latent vs. Manifest Variables Structural Equations with Latent Variables
The core of this methodology lies in the distinction between what we can measure and what we want to understand: : These are "hidden" or abstract constructs that