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#121 Exploring Bayesian Structural Equation Modeling, with Nathaniel Forde

Learning Bayesian Statistics

CHAPTER

Navigating Bayesian Structural Equation Modeling Challenges

This chapter explores the complexities of applying confirmatory factor analysis (CFA) and structural equation modeling (SEM) using the 'lavaan' package versus Bayesian methods. It highlights the advantages of Bayesian modeling, particularly in predictive checks and addressing model fit issues, while emphasizing the need for robust model validation and sensitivity analysis. Additionally, the chapter discusses practical applications in understanding employee engagement through Bayesian SEM, demonstrating how theoretical constructs can be illuminated through well-designed surveys.

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