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Model sa mešovitim efektima×Modeliranje strukturalnih jednačina (SEM)×
OblastStatistikaStatistika
PorodicaRegression modelLatent structure
Godina nastanka19821970
TvoracLaird & WareKarl Jöreskog (LISREL framework, 1970s)
TipMixed effects regressionLatent variable / causal modeling
Temeljni izvorLaird, 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
Drugi naziviLME, LMM, mixed model, random effects modelYapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
Srodne45
SažetakA 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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ScholarGateUporedite metode: Mixed Effects Model · SEM. Preuzeto 2026-06-19 sa https://scholargate.app/sr/compare