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Análise de Classes Latentes (ACL)×Modelagem de Equações Estruturais (MEE)×
ÁreaEstatísticaEstatística
FamíliaLatent structureLatent structure
Ano de origem19501970
Autor originalPaul F. LazarsfeldKarl Jöreskog (LISREL framework, 1970s)
TipoLatent variable / probabilistic clusteringLatent variable / causal modeling
Fonte seminalHagenaars, J. A. & McCutcheon, A. L. (Eds.) (2002). Applied Latent Class Analysis. Cambridge University Press. ISBN: 978-0521594516Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540
Outros nomesGizil Sınıf Analizi (LCA), latent class model, latent structure analysisYapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
Relacionados35
ResumoLatent 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.Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences.
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ScholarGateComparar métodos: LCA · SEM. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare