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Modelització Lineal Jeràrquica (HLM / Modelització Multinivell)×Model d'efectes mixts×Anàlisi de la variància d'un factor×
CampEstadísticaEstadísticaEstadística
FamíliaHypothesis testRegression modelHypothesis test
Any d'origen198619821925
Autor originalRaudenbush & Bryk (popularized); Goldstein (parallel development)Laird & WareRonald A. Fisher
TipusParametric nested-data regressionMixed effects regressionParametric mean comparison
Font seminalRaudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049Laird, N. M., & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38(4), 963–974. DOI ↗Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗
ÀliesHLM, MLM, multilevel modeling, multilevel analysisLME, LMM, mixed model, random effects modelone-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Relacionats444
ResumHierarchical 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.A 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.One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925.
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ScholarGateCompara mètodes: Hierarchical Linear Modeling · Mixed Effects Model · One-way ANOVA. Recuperat el 2026-06-19 de https://scholargate.app/ca/compare