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贝叶斯因子分析×贝叶斯网络×验证性因子分析 (CFA)×
领域贝叶斯贝叶斯统计学
方法族Bayesian methodsBayesian methodsLatent structure
起源年份200419881969
提出者Lopes & West (2004) for Bayesian model assessment in factor analysisJudea PearlKarl Jöreskog
类型Bayesian latent variable modelProbabilistic graphical modelConfirmatory latent variable model
开创性文献Lopes, H. F. & West, M. (2004). Bayesian Model Assessment in Factor Analysis. Statistica Sinica, 14(1), 41–67. link ↗Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363
别名Bayesian EFA, Bayesian CFA, Bayesçi Faktör Analizi, probabilistic factor analysisBayes network, belief network, probabilistic graphical model, directed graphical modelDoğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model
相关744
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.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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ScholarGate方法对比: Bayesian Factor Analysis · Bayesian Network · CFA. 于 2026-06-15 检索自 https://scholargate.app/zh/compare