Latent structureScale / measurement
Bayesian Confirmatory Factor Analysis (BCFA)
Bayesian confirmatory factor analysis tests a pre-specified factor structure using Bayesian inference. Instead of point estimates with p-values, it produces full posterior distributions for loadings, factor correlations, and residual variances, allowing the researcher to incorporate prior knowledge and propagate parameter uncertainty naturally.
Open in MethodMindSoonVideoSoon
Read the full method
Members only
Sign inSign in with a free account to read this section.
Sources
- Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232
- Muthén, B. & Asparouhov, T. (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), 313–335. DOI: 10.1037/a0026802 ↗
Related methods
Referenced by
Bayesian Construct ValidityBayesian Convergent ValidityBayesian Cronbach's alphaBayesian Discriminant AnalysisBayesian Discriminant ValidityBayesian EFABayesian Item AnalysisBayesian Latent Class AnalysisBayesian McDonald's omegaBayesian Measurement InvarianceBayesian Multidimensional ScalingBayesian Scale Development