Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models

J. David Singer

doi:10.2307/1165280

January 1, 1998Journal of Educational and Behavioral Statistics

Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models

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Key Points

Provide a comprehensive methodological guide and tutorial on using the SAS PROC MIXED procedure to specify, fit, and interpret multilevel, hierarchical linear, and individual growth models.
Demonstrates model parameterization, syntax specification, and covariance structure selection using SAS PROC MIXED for nested and longitudinal designs.
Illustrates the translation of multilevel equations into corresponding statistical software code for fixed and random effects.
Establishes that PROC MIXED effectively estimates parameters for two-level hierarchical models and longitudinal growth trajectories within a single general linear mixed-model framework.
Provides practical syntax templates and output interpretations for evaluating variance components, random slopes, and fixed effects in behavioral research.

Implication

Methodological tutorial demonstrates implementation of multilevel and growth models in SAS PROC MIXED, highlighting standardized statistical workflows for hierarchical data.

Abstract

Judith D. Singer, Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models, Journal of Educational and Behavioral Statistics, Vol. 23, No. 4 (Winter, 1998), pp. 323-355

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J. David Singer (1998) studied this question.

synapsesocial.com/papers/69ee775909d5923204fab9fc https://doi.org/10.2307/1165280

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Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models

Key Points

Implication

Abstract

Discussion

Cite This Study

Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models

Key Points

Implication

Abstract

Discussion

Cite This Study

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