Performance of Model Fit Indices in Bayesian Confirmatory Factor Analysis

• In Event: Methodology and Application in Structural Equation Modeling

Abstract

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 few studies have evaluated the characteristics of Bayesian fit indices. This simulation study investigated the performance of three fit indices (i.e., RMSEA, CFI, and TLI) in Bayesian confirmatory factor analysis (CFA) across different prior specifications, levels of model complexity, severity of misspecification, and sample sizes. Results show that for various prior specifications, Bayesian fit indices perform comparably to frequentist versions when sample sizes are large (e.g., N > 100).

Authors

• Kelly D. Edwards, University of Virginia

• Timothy R. Konold, University of Virginia