Description

This Master Prompt would focus on establishing the methodological foundations of Structural Equation Modeling (SEM) using IBM SPSS AMOS, with particular emphasis on covariance-based structural equation modeling (CB-SEM). It would guide researchers in understanding SEM as an integrated analytical framework for simultaneously examining relationships among observed and latent variables, distinguishing measurement models from structural models, and explaining the respective roles of SPSS and AMOS within a complete SEM workflow.

A major emphasis would be placed on methodological positioning. Researchers would determine when AMOS-based CB-SEM is appropriate for theory testing, confirmation and model validation; distinguish SEM from conventional regression, path analysis and exploratory factor analysis; and differentiate CB-SEM from PLS-SEM. The theme would establish the complete analytical architecture that connects theoretical specification, measurement assessment, model estimation, goodness-of-fit evaluation, structural relationships and interpretation. This is consistent with the reviewed literature, which identifies AMOS-based CB-SEM as a widely applied SEM approach and highlights methodological differences between CB-SEM and PLS-SEM.