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| 贝叶斯网络× | 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≠ | 1988 | 1969 |
| 提出者≠ | Judea Pearl | Karl Jöreskog |
| 类型≠ | Probabilistic graphical model | Confirmatory latent variable model |
| 开创性文献≠ | Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797 | Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363 |
| 别名≠ | Bayes network, belief network, probabilistic graphical model, directed graphical model | Doğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model |
| 相关 | 4 | 4 |
| 摘要≠ | A Bayesian network is a probabilistic graphical model, introduced by Judea Pearl in 1988, that encodes a set of variables and their conditional dependencies as a directed acyclic graph (DAG). Each node represents a variable; each directed edge encodes a direct probabilistic influence. By combining Bayes' rule with the graph's conditional independence structure, the model supports reasoning under uncertainty — computing the probability of any variable given observed evidence about others. | 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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