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पदानुक्रमिक रैखिक मॉडलिंग (एचएलएम / बहुस्तरीय मॉडलिंग)×मध्यस्थता विश्लेषण×
क्षेत्रसांख्यिकीसांख्यिकी
परिवारHypothesis testHypothesis test
उद्भव वर्ष19861986
प्रवर्तकRaudenbush & Bryk (popularized); Goldstein (parallel development)Baron & Kenny
प्रकारParametric nested-data regressionIndirect effects / path test
मौलिक स्रोतRaudenbush, 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 ↗
उपनामHLM, MLM, multilevel modeling, multilevel analysisindirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS)
संबंधित45
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.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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