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Hijerarhijsko linearno modeliranje (HLM / Multilevel Modeling)×Analiza medijacije×
OblastStatistikaStatistika
PorodicaHypothesis testHypothesis test
Godina nastanka19861986
TvoracRaudenbush & Bryk (popularized); Goldstein (parallel development)Baron & Kenny
TipParametric nested-data regressionIndirect effects / path test
Temeljni izvorRaudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049Baron, R. M. & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research. Journal of Personality and Social Psychology, 51(6), 1173–1182. link ↗
Drugi naziviHLM, MLM, multilevel modeling, multilevel analysisindirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS)
Srodne45
SažetakHierarchical 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.Mediation analysis is a statistical procedure that tests whether the effect of an independent variable X on an outcome Y operates wholly or partly through a third variable M, called the mediator. Formalised by Baron and Kenny in 1986, it decomposes the total effect of X on Y into a direct path (c′) and an indirect path (a × b), quantifying how much of the relationship is carried by the mediating mechanism.
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ScholarGateUporedite metode: Hierarchical Linear Modeling · Mediation Analysis. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare