Impact of Informative Priors on Model Fit Indices in Bayesian Confirmatory Factor Analysis

Assessing model fit is a key component of structural equation modeling (SEM); however, measures of fit in Bayesian SEM remain limited. Recently, versions of frequentist fit indices have been adapted for use in Bayesian models, but the impact of prior information on these fit indices remains unknown. This simulation study investigates the performance of three fit indices (RMSEA, CFI, and TLI) in Bayesian confirmatory factor analysis (CFA) across a variety of prior specifications that included different degrees of informativeness and inaccuracy. Results show that Bayesian fit indices are impacted by prior choice, particularly when sample sizes are small. We discuss implications of assessing model fit with Bayesian fit indices and provide recommendations for applied researchers.