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Latent Class Analysis (LCA)×Eksploratiivinen faktorianalyysi (EFA)×
TieteenalaTilastotiedeTilastotiede
MenetelmäperheLatent structureLatent structure
Syntyvuosi1950s–1968
KehittäjäPaul F. Lazarsfeld
TyyppiLatent variable / person-centered classificationLatent variable / dimension reduction
AlkuperäislähdeGoodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231. DOI ↗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. DOI ↗
RinnakkaisnimetLCA, latent class model, latent categorical analysis, finite mixture of multinomialscommon factor analysis, açımlayıcı faktör analizi, factor analysis
Liittyvät64
TiivistelmäLatent class analysis identifies unobserved subgroups — latent classes — within a population by finding patterns of responses across a set of categorical observed indicators. It is the categorical-variable counterpart of cluster analysis, but grounded in an explicit probabilistic model, and is widely used in social, health, and behavioral sciences to discover typologies in survey or diagnostic data.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.
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ScholarGateVertaile menetelmiä: Latent Class Analysis · EFA. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare