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| Analyse factorielle confirmatoire bayésienne (AFCB)× | Analyse Factorielle Confirmatoire (AFC)× | |
|---|---|---|
| Domaine | Psychométrie | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 2007–2012 | 1969 |
| Auteur d'origine≠ | Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov | Karl Gustav Jöreskog |
| Type≠ | Bayesian latent variable model | Hypothesis-testing latent variable model |
| Source fondatrice≠ | Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Alias | BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Apparentées | 4 | 4 |
| 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. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
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