方法对比
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| 贝叶斯因子分析× | 结构方程模型 (SEM)× | |
|---|---|---|
| 领域≠ | 贝叶斯 | 统计学 |
| 方法族≠ | Bayesian methods | Latent structure |
| 起源年份≠ | 2004 | 1970 |
| 提出者≠ | Lopes & West (2004) for Bayesian model assessment in factor analysis | Karl Jöreskog (LISREL framework, 1970s) |
| 类型≠ | Bayesian latent variable model | Latent variable / causal modeling |
| 开创性文献≠ | Lopes, H. F. & West, M. (2004). Bayesian Model Assessment in Factor Analysis. Statistica Sinica, 14(1), 41–67. link ↗ | Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540 |
| 别名 | Bayesian EFA, Bayesian CFA, Bayesçi Faktör Analizi, probabilistic factor analysis | Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling |
| 相关≠ | 7 | 5 |
| 摘要≠ | Bayesian Factor Analysis is a probabilistic latent-variable method that places prior distributions on the factor loading matrix and the residual variances, then infers a full posterior over these parameters from the observed data. Developed prominently in the Bayesian framework by Lopes and West (2004), it extends classical exploratory and confirmatory factor analysis by quantifying uncertainty in every estimated loading rather than reporting single point estimates. | Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences. |
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