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| 잠재계층분석 (Latent Class Analysis, LCA)× | 탐색적 요인 분석 (EFA)× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1950 | — |
| 창시자≠ | Paul F. Lazarsfeld | — |
| 유형≠ | Latent variable / probabilistic clustering | Latent variable / dimension reduction |
| 원전≠ | 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. DOI ↗ |
| 별칭 | Gizil Sınıf Analizi (LCA), latent class model, latent structure analysis | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| 관련≠ | 3 | 4 |
| 요약≠ | 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. |
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