手法を比較

	階層線形モデリング（HLM / マルチレベルモデリング）	一元配置分散分析	反復測定分散分析
分野	統計学	統計学	統計学
系統	Hypothesis test	Hypothesis test	Hypothesis test
提唱年	1986	1925	1992
提唱者	Raudenbush & Bryk (popularized); Goldstein (parallel development)	Ronald A. Fisher	Girden (textbook treatment); Field (2013)
種類	Parametric nested-data regression	Parametric mean comparison	Parametric within-subjects mean comparison
原典	Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.	Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185
別名	HLM, MLM, multilevel modeling, multilevel analysis	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA	within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA
関連	4	4	4
概要	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.	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.	Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013).