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| Бейсовски Омега на Макдоналд× | Байесов потвърдителен факторен анализ (BCFA)× | |
|---|---|---|
| Област | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Година на възникване≠ | 1999 (omega); 2010s (Bayesian estimation) | 2007–2012 |
| Създател≠ | R. P. McDonald (omega); Bayesian extension developed by Kelley, Pornprasertmanit, and others | Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov |
| Тип≠ | Reliability / internal consistency estimation | Bayesian latent variable model |
| Основополагащ източник≠ | Kelley, K. & Pornprasertmanit, S. (2016). Confidence intervals for population reliability coefficients: Evaluation of methods, recommendations, and software for composite measures. Psychological Methods, 21(1), 69–92. DOI ↗ | Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232 |
| Други названия | Bayesian omega, Bayesian composite reliability, posterior omega, Bayesian omega total | BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA |
| Свързани≠ | 3 | 4 |
| Резюме≠ | Bayesian McDonald's omega applies Bayesian statistical estimation to the omega reliability coefficient, yielding a full posterior distribution over omega rather than a single point estimate. This provides credible intervals and probabilistic uncertainty quantification for the reliability of a composite or scale score, making it especially useful for small samples and complex factor structures. | 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. |
| ScholarGateНабор от данни ↗ |
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