Comparer des méthodes

	Développement d'échelles bayésiennes	Analyse factorielle exploratoire (AFE)
Domaine	Psychométrie	Statistique
Famille	Latent structure	Latent structure
Année d'origine	1990s–2000s	—
Auteur d'origine	Harold Jeffreys, expanded into psychometrics by Mislevy and colleagues	—
Type	Bayesian probabilistic scale construction	Latent variable / dimension reduction
Source fondatrice	De Ayala, R. J. (2009). The Theory and Practice of Item Response Theory. Guilford Press. ISBN: 978-1593858698	Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299.
Alias	Bayesian psychometric scale construction, Bayesian measurement modeling, Bayesian item development, BSD	common factor analysis, açımlayıcı faktör analizi, factor analysis
Apparentées	5	4
Résumé	Bayesian scale development applies Bayesian statistical inference to the construction and evaluation of psychometric scales. Rather than relying on single point estimates of item and person parameters, it produces full posterior distributions that quantify uncertainty, incorporate prior knowledge, and support principled decisions about item retention, reliability, and validity in small or complex samples.	Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance.