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媒介分析×多層レベルモデリング×
分野統計学研究統計
系統Hypothesis testProcess / pipeline
提唱年19861992
提唱者Baron & KennyAnthony Bryk and Stephen Raudenbush
種類Indirect effects / path testMethod
原典Baron, 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 ↗
別名indirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS)HLM, mixed-effects models, random effects models, MLM
関連53
概要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.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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ScholarGate手法を比較: Mediation Analysis · Multilevel Modeling. 2026-06-18に以下より取得 https://scholargate.app/ja/compare