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Phân tích trung gian×Mô hình đa cấp×
Lĩnh vựcThống kêThống kê nghiên cứu
HọHypothesis testProcess / pipeline
Năm ra đời19861992
Người khởi xướngBaron & KennyAnthony Bryk and Stephen Raudenbush
LoạiIndirect effects / path testMethod
Công trình gốcBaron, 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 ↗Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical Linear Models: Applications and Data Analysis Methods. SAGE Publications. DOI ↗
Tên gọi khácindirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS)HLM, mixed-effects models, random effects models, MLM
Liên quan53
Tóm tắtMediation 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.Multilevel modeling (also called hierarchical linear modeling, mixed-effects modeling) is a statistical framework for analyzing data organized in nested or clustered structures—students within schools, patients within hospitals, repeated measures within individuals. Developed by Bryk and Raudenbush (1992), it accounts for dependency among observations and partitions variance into levels (within-cluster and between-cluster), enabling valid inference and revealing context effects. Essential in education, medicine, organizational research, and any field where data have natural hierarchies.
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ScholarGateSo sánh phương pháp: Mediation Analysis · Multilevel Modeling. Truy cập ngày 2026-06-18 từ https://scholargate.app/vi/compare