方法对比
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| 贝叶斯判别效度评估× | 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≠ | 2020 (Bayesian HTMT formalization); 1959 (discriminant validity concept) | 2007–2012 |
| 提出者≠ | Adaptation of Campbell & Fiske (1959) discriminant validity into Bayesian CFA framework; Bayesian HTMT formalization by Garnier-Villarreal & Jorgensen (2020) | Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov |
| 类型≠ | Validity assessment | Bayesian latent variable model |
| 开创性文献≠ | Garnier-Villarreal, M. & Jorgensen, T. D. (2020). Adapting fit indices for Bayesian structural equation modeling: Comparison to maximum likelihood. Psychological Methods, 25(1), 46–70. DOI ↗ | Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232 |
| 别名 | Bayesian HTMT, Bayesian HTMTb, Bayesian discriminant evidence, Bayesian CFA discriminant validity | BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA |
| 相关≠ | 6 | 4 |
| 摘要≠ | Bayesian discriminant validity assessment evaluates whether two theoretically distinct latent constructs are empirically separable, using posterior distributions and credible intervals rather than single-point null-hypothesis tests. It is applied within Bayesian confirmatory factor analysis or via the Bayesian heterotrait-monotrait ratio (HTMTb) to determine whether constructs measuring different traits are sufficiently differentiated. | 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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