方法对比
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| 贝叶斯结构效度评估× | 贝叶斯验证性因子分析 (BCFA)× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1955 / 2012 | 2007–2012 |
| 提出者≠ | Cronbach & Meehl (validity framework); Muthén & Asparouhov (Bayesian SEM extension) | Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov |
| 类型≠ | Validity assessment / Bayesian inference | Bayesian latent variable model |
| 开创性文献≠ | Muthén, B. & Asparouhov, T. (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), 313–335. DOI ↗ | Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232 |
| 别名 | Bayesian validity analysis, Bayesian CFA-based validity, Bayesian structural validity, posterior construct validity | BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA |
| 相关≠ | 6 | 4 |
| 摘要≠ | Bayesian construct validity assessment uses Bayesian confirmatory factor analysis and related Bayesian structural equation models to evaluate whether a scale or test measures the intended latent construct. It yields full posterior distributions for factor loadings, structural coefficients, and model-fit indices rather than single point estimates, enabling more nuanced and uncertainty-aware validity conclusions. | 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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