Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Anthony Recchia
Title: R-Squared Measures for Two-Level Hierarchical Linear Models Using SAS
Abstract: The hierarchical linear model (HLM) is the primary tool of multilevel analysis, a set of techniques for examining data with nested sources of variability. The concept of R2 from classical multiple regression analysis cannot be applied directly to HLMs without certain undesirable results. However, multilevel analogues have been formulated. The goal here is to demonstrate a SAS macro that will calculate estimates of these quantities for a two-level HLM that has been fit with SAS's linear mixed modeling procedure, PROC MIXED.

Page views:: 17985. Submitted: 2009-07-02. Published: 2010-01-12.
Paper: R-Squared Measures for Two-Level Hierarchical Linear Models Using SAS     Download PDF (Downloads: 20505)
Supplements:
hlmrsq.sas: SAS source code Download (Downloads: 2146; 21KB)
v32c02.sas: SAS replication code for the paper Download (Downloads: 1909; 5KB)

DOI: 10.18637/jss.v032.c02

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.