Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise de Classes Latentes (ACL)× | Análise Fatorial Exploratória (AFE)× | |
|---|---|---|
| Área | Estatística | Estatística |
| Família | Latent structure | Latent structure |
| Ano de origem≠ | 1950 | — |
| Autor original≠ | Paul F. Lazarsfeld | — |
| Tipo≠ | Latent variable / probabilistic clustering | Latent variable / dimension reduction |
| Fonte seminal≠ | 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 ↗ |
| Outros nomes | Gizil Sınıf Analizi (LCA), latent class model, latent structure analysis | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Relacionados≠ | 3 | 4 |
| Resumo≠ | 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. |
| ScholarGateConjunto de dados ↗ |
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