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Hausmanov test specifikacije (FE vs RE)×Hijerarhijsko linearno modeliranje (HLM / Multilevel Modeling)×
OblastEkonometrijaStatistika
PorodicaRegression modelHypothesis test
Godina nastanka19781986
TvoracJerry A. HausmanRaudenbush & Bryk (popularized); Goldstein (parallel development)
TipSpecification test for panel data modelsParametric nested-data regression
Temeljni izvorHausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271. DOI ↗Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049
Drugi naziviHausman specification test, FE vs RE test, Durbin-Wu-Hausman test, Hausman Spesifikasyon Testi (FE vs RE)HLM, MLM, multilevel modeling, multilevel analysis
Srodne54
SažetakThe Hausman test is a specification test, introduced by Jerry A. Hausman in 1978, that decides between the fixed-effects (FE) and random-effects (RE) estimators in panel data models. The null hypothesis is that the random-effects estimator is consistent and efficient and should be preferred; the alternative is that random effects is inconsistent and fixed effects is required because the unit-specific effects are correlated with the explanatory variables.Hierarchical Linear Modeling (HLM), also known as Multilevel Modeling (MLM), is a parametric statistical method for analyzing nested or clustered data — for example students within classrooms, patients within hospitals, or employees within organizations. Formalized by Raudenbush and Bryk in their 2002 seminal text (building on work from the mid-1980s), HLM simultaneously estimates individual-level and group-level effects while correctly partitioning variance across levels.
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ScholarGateUporedite metode: Hausman Test · Hierarchical Linear Modeling. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare