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Decoding Prior Sensitivity in Bayesian Structural Equation Modeling for Sparse Factor Loading Structures
Statistical Methods and Data Analysis

Understanding Prior Sensitivity in Bayesian Structural Equation Modeling

Liang’s (2020) study on Bayesian Structural Equation Modeling (BSEM) focuses on the use of small-variance normal distribution priors (BSEM-N) for analyzing sparse factor loading structures. This research provides insights into how different priors affect model performance, offering valuable guidance for researchers employing BSEM in their work. Background Bayesian Structural Equation …