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| 贝叶斯分层模型× | 验证性因子分析 (CFA)× | |
|---|---|---|
| 领域≠ | 贝叶斯 | 统计学 |
| 方法族≠ | Bayesian methods | Latent structure |
| 起源年份≠ | 2006 | 1969 |
| 提出者≠ | Gelman & Hill (2006); Bayesian multilevel tradition | Karl Jöreskog |
| 类型≠ | hierarchical probabilistic model | Confirmatory latent variable model |
| 开创性文献≠ | Gelman, A. & Hill, J. (2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press. DOI ↗ | Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363 |
| 别名≠ | multilevel Bayes, Bayesian multilevel model, Bayesian HLM, partial pooling model | Doğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model |
| 相关 | 4 | 4 |
| 摘要≠ | Bayesian hierarchical modelling, popularised by Gelman and Hill (2006), is a Bayesian approach to nested data structures — such as students within schools within districts — that estimates separate parameters at each level while allowing those levels to share statistical strength through a mechanism called partial pooling. Where a classical hierarchical linear model treats group means as fixed unknown quantities, the Bayesian version places hyperprior distributions on those group means so that information flows freely across levels, producing more reliable group-level estimates whenever any individual group has few observations. | Confirmatory factor analysis tests whether a researcher-specified factor structure fits the observed data. Formalised by Karl Jöreskog in 1969, it is the measurement-model step within structural equation modelling and is the standard tool for validating the factorial structure of scales and questionnaires before comparing groups or estimating latent relationships. |
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