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	बेयसियन एक्सप्लोरेटरी फैक्टर एनालिसिस (BEFA)	बायेसियन कन्फर्मेटरी फैक्टर एनालिसिस (BCFA)
क्षेत्र	मनोमिति	मनोमिति
परिवार	Latent structure	Latent structure
उद्भव वर्ष	2004 (Bayesian formulation); factor analysis roots: 1904	2007–2012
प्रवर्तक	Lopes & West (seminal Bayesian treatment); roots in classical factor analysis (Spearman, 1904)	Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov
प्रकार	Probabilistic latent variable model	Bayesian latent variable model
मौलिक स्रोत	Lopes, H. F. & West, M. (2004). Bayesian model assessment in factor analysis. Statistica Sinica, 14(1), 41–67.	Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232
उपनाम	Bayesian factor analysis, BEFA, Bayesian common factor model, probabilistic factor analysis	BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA
संबंधित	4	4
सारांश	Bayesian exploratory factor analysis applies a full probabilistic framework to the common factor model. By placing prior distributions over factor loadings and unique variances, it yields posterior distributions rather than point estimates, quantifies uncertainty around every loading, and can treat the number of factors as an unknown to be inferred from data.	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.