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ベイズ構造方程式モデリング(BSEM)×ベイズ回帰×確認的因子分析(CFA)×
分野ベイズベイズ統計学
系統Bayesian methodsBayesian methodsLatent structure
提唱年20121969
提唱者Bengt Muthén & Tihomir AsparouhovKarl Jöreskog
種類Bayesian latent variable modelBayesian linear modelConfirmatory latent variable model
原典Muthén, B. & Asparouhov, T. (2012). Bayesian SEM: A More Flexible Representation of Substantive Theory. Psychological Methods, 17(3), 313–335. link ↗Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363
別名BSEM, Bayesian latent variable model, approximate zero constraints SEM, Bayesçi Yapısal Eşitlik Modelibayesian linear regression, probabilistic regression, bayesian regresyonDoğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model
関連624
概要Bayesian SEM, introduced by Muthén and Asparouhov in 2012, extends classical structural equation modeling by placing prior distributions on factor loadings, path coefficients, and covariances. Instead of returning a single maximum-likelihood estimate, it uses Markov chain Monte Carlo to produce a full posterior distribution for every parameter, enabling principled uncertainty quantification in models with latent variables.Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off.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手法を比較: Bayesian SEM · Bayesian Regression · CFA. 2026-06-19に以下より取得 https://scholargate.app/ja/compare