Comparer des méthodes

	Modélisation Bayésienne par Équations Structurelles (BSEM)	Analyse Factorielle Confirmatoire (AFC)
Domaine	Bayésien	Statistique
Famille	Bayesian methods	Latent structure
Année d'origine	2012	1969
Auteur d'origine	Bengt Muthén & Tihomir Asparouhov	Karl Jöreskog
Type	Bayesian latent variable model	Confirmatory latent variable model
Source fondatrice	Muthén, B. & Asparouhov, T. (2012). Bayesian SEM: A More Flexible Representation of Substantive Theory. Psychological Methods, 17(3), 313–335.	Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363
Alias	BSEM, Bayesian latent variable model, approximate zero constraints SEM, Bayesçi Yapısal Eşitlik Modeli	Doğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model
Apparentées	6	4
Résumé	Bayesian SEM, introduced by Muthén and Asparouhov in 2012, extends classical structural equation modeling by placing prior distributions on factor loadings, path coefficients, and covariances. Instead of returning a single maximum-likelihood estimate, it uses Markov chain Monte Carlo to produce a full posterior distribution for every parameter, enabling principled uncertainty quantification in models with latent variables.	Confirmatory factor analysis tests whether a researcher-specified factor structure fits the observed data. Formalised by Karl Jöreskog in 1969, it is the measurement-model step within structural equation modelling and is the standard tool for validating the factorial structure of scales and questionnaires before comparing groups or estimating latent relationships.