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Latent structureMultivariate analysis

Latent Class Analysis (LCA)

Latent 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.

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Lähteet

  1. Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231. DOI: 10.1093/biomet/61.2.215
  2. Lazarsfeld, P. F. & Henry, N. W. (1968). Latent Structure Analysis. Houghton Mifflin. link

Näin viittaat tähän sivuun

ScholarGate. (2026, June 3). Latent Class Analysis. ScholarGate. https://scholargate.app/fi/statistics/latent-class-analysis

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Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

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Tähän viittaavat

ScholarGateLatent Class Analysis (Latent Class Analysis). Haettu 2026-06-15 osoitteesta https://scholargate.app/fi/statistics/latent-class-analysis · Aineisto: https://doi.org/10.5281/zenodo.20539026