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| Régression bayésienne× | Analyse Factorielle Confirmatoire (AFC)× | |
|---|---|---|
| Domaine≠ | Bayésien | Statistique |
| Famille≠ | Bayesian methods | Latent structure |
| Année d'origine≠ | — | 1969 |
| Auteur d'origine≠ | — | Karl Jöreskog |
| Type≠ | Bayesian linear model | Confirmatory latent variable model |
| Source fondatrice≠ | 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: 978-1439840955 | Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363 |
| Alias | bayesian linear regression, probabilistic regression, bayesian regresyon | Doğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model |
| Apparentées≠ | 2 | 4 |
| Résumé≠ | 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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