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Réseau bayésien×Analyse Factorielle Confirmatoire (AFC)×
DomaineBayésienStatistique
FamilleBayesian methodsLatent structure
Année d'origine19881969
Auteur d'origineJudea PearlKarl Jöreskog
TypeProbabilistic graphical modelConfirmatory latent variable model
Source fondatricePearl, 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
AliasBayes network, belief network, probabilistic graphical model, directed graphical modelDoğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model
Apparentées44
RésuméA 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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ScholarGateComparer des méthodes: Bayesian Network · CFA. Consulté le 2026-06-15 sur https://scholargate.app/fr/compare