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| Analyse factorielle confirmatoire bayésienne (AFCB)× | Test bayésien d'invariance de la mesure× | |
|---|---|---|
| Domaine | Psychométrie | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 2007–2012 | 2013 |
| Auteur d'origine≠ | Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov | Bengt Muthen, Tihomir Asparouhov, Rens Van de Schoot |
| Type≠ | Bayesian latent variable model | Bayesian multigroup latent variable test |
| Source fondatrice≠ | Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232 | 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. DOI ↗ |
| Alias | BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA | Bayesian MI, approximate measurement invariance, Bayesian multigroup CFA invariance, BSEM measurement invariance |
| Apparentées≠ | 4 | 6 |
| Résumé≠ | 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. | 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. |
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