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| Διερευνητική Παραγοντική Ανάλυση Bayes (BEFA)× | Διεσταλμένη Διερευνητική Ανάλυση Παραγόντων (BCFA)× | |
|---|---|---|
| Πεδίο | Ψυχομετρία | Ψυχομετρία |
| Οικογένεια | Latent structure | Latent structure |
| Έτος προέλευσης≠ | 2004 (Bayesian formulation); factor analysis roots: 1904 | 2007–2012 |
| Δημιουργός≠ | Lopes & West (seminal Bayesian treatment); roots in classical factor analysis (Spearman, 1904) | Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov |
| Τύπος≠ | Probabilistic latent variable model | Bayesian latent variable model |
| Θεμελιώδης πηγή≠ | Lopes, H. F. & West, M. (2004). Bayesian model assessment in factor analysis. Statistica Sinica, 14(1), 41–67. link ↗ | Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232 |
| Εναλλακτικές ονομασίες | Bayesian factor analysis, BEFA, Bayesian common factor model, probabilistic factor analysis | BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA |
| Συναφείς | 4 | 4 |
| Σύνοψη≠ | 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. |
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