قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| تحليل العوامل الاستكشافي البيزي (BEFA)× | تحليل العوامل التأكيدي البايزي (BCFA)× | |
|---|---|---|
| المجال | القياس النفسي | القياس النفسي |
| العائلة | Latent structure | Latent structure |
| سنة النشأة≠ | 2004 (Bayesian formulation); factor analysis roots: 1904 | 2007–2012 |
| صاحب الطريقة≠ | Lopes & West (seminal Bayesian treatment); roots in classical factor analysis (Spearman, 1904) | Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov |
| النوع≠ | Probabilistic latent variable model | Bayesian latent variable model |
| المصدر التأسيسي≠ | 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 |
| الأسماء البديلة | Bayesian factor analysis, BEFA, Bayesian common factor model, probabilistic factor analysis | BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA |
| ذات صلة | 4 | 4 |
| الملخص≠ | 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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