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Modellazione Lineare Gerarchica (HLM / Modellazione Multilivello)×Analisi della Varianza a una Via×ANOVA per misure ripetute×
CampoStatisticaStatisticaStatistica
FamigliaHypothesis testHypothesis testHypothesis test
Anno di origine198619251992
IdeatoreRaudenbush & Bryk (popularized); Goldstein (parallel development)Ronald A. FisherGirden (textbook treatment); Field (2013)
TipoParametric nested-data regressionParametric mean comparisonParametric within-subjects mean comparison
Fonte seminaleRaudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185
AliasHLM, MLM, multilevel modeling, multilevel analysisone-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVAwithin-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA
Correlati444
SintesiHierarchical 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.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.Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013).
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ScholarGateConfronta i metodi: Hierarchical Linear Modeling · One-way ANOVA · Repeated-measures ANOVA. Consultato il 2026-06-19 da https://scholargate.app/it/compare