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Model zmiešaných efektov×Modelovanie štruktúrnymi rovnicami (SEM)×
OdborŠtatistikaŠtatistika
RodinaRegression modelLatent structure
Rok vzniku19821970
TvorcaLaird & WareKarl Jöreskog (LISREL framework, 1970s)
TypMixed effects regressionLatent variable / causal modeling
Pôvodný zdrojLaird, N. M., & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38(4), 963–974. DOI ↗Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540
Ďalšie názvyLME, LMM, mixed model, random effects modelYapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
Príbuzné45
ZhrnutieA mixed effects model (or linear mixed model) extends ordinary regression by including both fixed effects — population-level parameters shared by all observations — and random effects that capture subject-, group-, or cluster-level variability. It is the standard tool for repeated-measures, longitudinal, and multilevel data where observations within the same unit are correlated.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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ScholarGatePorovnať metódy: Mixed Effects Model · SEM. Získané 2026-06-19 z https://scholargate.app/sk/compare