EconPapers    
Economics at your fingertips  
 

R-Squared Measures for Two-Level Hierarchical Linear Models Using SAS

Anthony Recchia

Journal of Statistical Software, 2010, vol. 032, issue c02

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.

Date: 2010-01-12
References: View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v032c02/v32c02.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... e/v032c02/hlmrsq.sas
https://www.jstatsoft.org/index.php/jss/article/do ... e/v032c02/v32c02.sas

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:032:c02

DOI: 10.18637/jss.v032.c02

Access Statistics for this article

Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis

More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().

 
Page updated 2025-03-19
Handle: RePEc:jss:jstsof:v:032:c02