Methoden vergleichen

	Latent Class Analysis (LCA)	Strukturelle Gleichungsmodellierung (SEM)
Fachgebiet	Statistik	Statistik
Familie	Latent structure	Latent structure
Entstehungsjahr	1950	1970
Urheber	Paul F. Lazarsfeld	Karl Jöreskog (LISREL framework, 1970s)
Typ	Latent variable / probabilistic clustering	Latent variable / causal modeling
Wegweisende Quelle	Hagenaars, J. A. & McCutcheon, A. L. (Eds.) (2002). Applied Latent Class Analysis. Cambridge University Press. ISBN: 978-0521594516	Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540
Aliasnamen	Gizil Sınıf Analizi (LCA), latent class model, latent structure analysis	Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
Verwandt	3	5
Zusammenfassung	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.	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.