手法を比較

	潜在クラス分析（LCA）	因子分析（EFA）
分野	統計学	統計学
系統	Latent structure	Latent structure
提唱年	1950	—
提唱者	Paul F. Lazarsfeld	—
種類	Latent variable / probabilistic clustering	Latent variable / dimension reduction
原典	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.
別名	Gizil Sınıf Analizi (LCA), latent class model, latent structure analysis	common factor analysis, açımlayıcı faktör analizi, factor analysis
関連	3	4
概要	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.