Comparer des méthodes

	Analyse de classes latentes (ACL)	Analyse factorielle exploratoire (AFE)
Domaine	Statistique	Statistique
Famille	Latent structure	Latent structure
Année d'origine	1950	—
Auteur d'origine	Paul F. Lazarsfeld	—
Type	Latent variable / probabilistic clustering	Latent variable / dimension reduction
Source fondatrice	Hagenaars, J. A. & McCutcheon, A. L. (Eds.) (2002). Applied Latent Class Analysis. Cambridge University Press. ISBN: 978-0521594516	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	Gizil Sınıf Analizi (LCA), latent class model, latent structure analysis	common factor analysis, açımlayıcı faktör analizi, factor analysis
Apparentées	3	4
Résumé	Latent class analysis is a probabilistic model-based clustering technique that identifies unobserved subgroups — latent classes — within a population on the basis of patterns of categorical, binary, or ordinal indicator responses. Originating in sociological measurement theory with Lazarsfeld's latent structure work around 1950 and formalised computationally by Goodman in the 1970s, it is widely used in the social, health, and behavioural sciences to reveal hidden population heterogeneity.	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.