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पदानुक्रमिक रैखिक मॉडलिंग (एचएलएम / बहुस्तरीय मॉडलिंग)×एक-तरफ़ा विचरण विश्लेषण×
क्षेत्रसांख्यिकीसांख्यिकी
परिवारHypothesis testHypothesis test
उद्भव वर्ष19861925
प्रवर्तकRaudenbush & Bryk (popularized); Goldstein (parallel development)Ronald A. Fisher
प्रकारParametric nested-data regressionParametric mean comparison
मौलिक स्रोतRaudenbush, 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 ↗
उपनामHLM, MLM, multilevel modeling, multilevel analysisone-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
संबंधित44
सारांशHierarchical 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.
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ScholarGateविधियों की तुलना करें: Hierarchical Linear Modeling · One-way ANOVA. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare