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Educational Hierarchical Linear Modeling

Educational hierarchical linear modeling (HLM) is a multilevel regression framework for data in which students are nested within classrooms and classrooms within schools. Formalized for education by Raudenbush and Bryk, it lets the intercept and slopes of a student-level regression vary across schools, simultaneously estimating student-level relationships, school-level relationships, and the cross-level interactions between them — while producing correct standard errors that single-level regression on clustered data cannot.

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Hierarchical Linear Modeling of Students Nested in Classrooms and Schools

Taxonomisk metodpost · regression-model / education

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. · ISBN 9780761919049
Bryk, A. S., & Raudenbush, S. W. (1987). Application of hierarchical linear models to assessing change. Psychological Bulletin, 101(1), 147–158. · DOI 10.1037/0033-2909.101.1.147

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Same method familyEducational Growth Curve Modelingmachine-suggested · Relational suggestion, not evidence.Same method familyHierarchical Linear Modelmachine-suggested · Relational suggestion, not evidence.See alsoHierarchical Linear Modelingmachine-suggested · Relational suggestion, not evidence.See alsoMultilevel Modelingmachine-suggested · Relational suggestion, not evidence.