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تحلیل میانجیگری چندسطحی×مدل‌سازی خطی سلسله‌مراتبی (HLM / مدل‌سازی چندسطحی)×
حوزهآمارآمار
خانوادهHypothesis testHypothesis test
سال پیدایش20031986
پدیدآورKenny, Korchmaros & BolgerRaudenbush & Bryk (popularized); Goldstein (parallel development)
نوعMultilevel structural modelParametric nested-data regression
منبع بنیادینKenny, D. A., Korchmaros, J. D., & Bolger, N. (2003). Lower level mediation in multilevel models. Psychological Methods, 8(2), 115–128. DOI ↗Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049
نام‌های دیگرmultilevel mediation, hierarchical mediation, cross-level mediation, 1-1-1 mediationHLM, MLM, multilevel modeling, multilevel analysis
مرتبط84
خلاصهMultilevel mediation analysis is a parametric structural method that estimates indirect (mediated) effects within hierarchically nested data, such as students within schools or employees within organisations. Formalised for lower-level mediation in multilevel models by Kenny, Korchmaros and Bolger (2003), it simultaneously handles individual-level (1-1-1) and group-level (2-2-1 or 2-1-1) mediation pathways in a single coherent framework.Hierarchical 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.
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ScholarGateمقایسهٔ روش‌ها: Multilevel Mediation Analysis · Hierarchical Linear Modeling. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare