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| Analisis Faktor Konfirmatori Bayesian (BCFA)× | Analisis Faktor Eksploratori Bayesian (BEFA)× | |
|---|---|---|
| Bidang | Psikometri | Psikometri |
| Keluarga | Latent structure | Latent structure |
| Tahun asal≠ | 2007–2012 | 2004 (Bayesian formulation); factor analysis roots: 1904 |
| Pencetus≠ | Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov | Lopes & West (seminal Bayesian treatment); roots in classical factor analysis (Spearman, 1904) |
| Tipe≠ | Bayesian latent variable model | Probabilistic latent variable model |
| Sumber perintis≠ | Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232 | Lopes, H. F. & West, M. (2004). Bayesian model assessment in factor analysis. Statistica Sinica, 14(1), 41–67. link ↗ |
| Alias | BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA | Bayesian factor analysis, BEFA, Bayesian common factor model, probabilistic factor analysis |
| Terkait | 4 | 4 |
| Ringkasan≠ | 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 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. |
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