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Latent Class Analysis (LCA)×Struktuurvõrrandite modelleerimine (SEM)×
ValdkondStatistikaStatistika
PerekondLatent structureLatent structure
Tekkeaasta19501970
LoojaPaul F. LazarsfeldKarl Jöreskog (LISREL framework, 1970s)
TüüpLatent variable / probabilistic clusteringLatent variable / causal modeling
AlgallikasHagenaars, 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
RööpnimetusedGizil Sınıf Analizi (LCA), latent class model, latent structure analysisYapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
Seotud35
KokkuvõteLatent 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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ScholarGateVõrdle meetodeid: LCA · SEM. Loetud 2026-06-15 aadressilt https://scholargate.app/et/compare