方法对比
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| 贝叶斯收敛效度× | 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≠ | 2000s–2010s | 2007–2012 |
| 提出者≠ | Building on Campbell & Fiske (1959) convergent validity; Bayesian extension developed in modern psychometrics literature | Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov |
| 类型≠ | Validity assessment / Bayesian inference | Bayesian latent variable model |
| 开创性文献≠ | Levy, R. & Mislevy, R. J. (2016). Bayesian Psychometric Modeling. CRC Press. ISBN: 978-1466500952 | Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232 |
| 别名 | Bayesian convergent validity analysis, Bayesian MTMM convergent validity, Bayesian multitrait convergent validity, BCV | BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA |
| 相关≠ | 6 | 4 |
| 摘要≠ | Bayesian convergent validity applies Bayesian statistical inference to assess whether different measures of the same construct converge as theory predicts. Rather than a single-point correlation estimate, it yields a full posterior distribution over the convergent correlation, enabling probability statements about the magnitude of shared variance between theoretically related measures. | 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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