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分层线性模型 (HLM / 多层模型)×单因素方差分析×结构方程模型 (SEM)×
领域统计学统计学统计学
方法族Hypothesis testHypothesis testLatent structure
起源年份198619251970
提出者Raudenbush & Bryk (popularized); Goldstein (parallel development)Ronald A. FisherKarl Jöreskog (LISREL framework, 1970s)
类型Parametric nested-data regressionParametric mean comparisonLatent variable / causal modeling
开创性文献Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540
别名HLM, MLM, multilevel modeling, multilevel analysisone-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVAYapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
相关445
摘要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.Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences.
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ScholarGate方法对比: Hierarchical Linear Modeling · One-way ANOVA · SEM. 于 2026-06-19 检索自 https://scholargate.app/zh/compare