Comparer des méthodes

	Test bayésien d'invariance de la mesure	Analyse factorielle confirmatoire bayésienne (AFCB)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	2013	2007–2012
Auteur d'origine	Bengt Muthen, Tihomir Asparouhov, Rens Van de Schoot	Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov
Type	Bayesian multigroup latent variable test	Bayesian latent variable model
Source fondatrice	Van de Schoot, R., Kluytmans, A., Tummers, L., Lugtig, P., Hox, J., & Muthen, B. (2013). Facing off with Scylla and Charybdis: a comparison of scalar, partial, and the novel possibility of approximate measurement invariance. Frontiers in Psychology, 4, 770.	Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232
Alias	Bayesian MI, approximate measurement invariance, Bayesian multigroup CFA invariance, BSEM measurement invariance	BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA
Apparentées	6	4
Résumé	Bayesian measurement invariance testing evaluates whether a scale's factor loadings and item intercepts are equivalent across groups, using a Bayesian framework that allows parameters to deviate from strict equality by a small, probabilistically specified amount rather than imposing an exact constraint.	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.