Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis

Journal of Educational and Behavioral Statistics

Volumn 38, Issue 1, 2013, Pages 3-31

  Luo, Wen ^a   Azen, Razia ^a  

^a UNIVERSITY OF WISCONSIN MILWAUKEE   (United States)

Author keywords

dominance analysis; ECLS K; HLM; relative importance of predictors

Indexed keywords

EID: 84871670675     PISSN: 10769986     EISSN: None     Source Type: Journal    
DOI: 10.3102/1076998612458319     Document Type: Article

References (23)

1. Azen R.,Budescu D. V.The dominance analysis approach for comparing predictors in multiple regression.Psychological Methods. 2003;8:129-148.
2. Azen R.,Budescu D. V.The SAGE handbook of quantitative methods in psychology. Millsap R. E.Maydeu-Olivares A., ed. Thousand Oaks, CA: Sage; 2009:285-310.
3. Azen R.,Traxel N. M.Using dominance analysis to determine predictor importance in logistic regression.Journal of Educational and Behavioral Statistics. 2009;34:319-347.
4. Bring J.How to standardize regression coefficients.The American Statistician. 1994;48:209-213.
5. Budescu D. V.Dominance analysis: A new approach to the problem of relative importance of predictors in multiple regression.Psychological Bulletin. 1993;114:542-551.
6. Chevan A.,Sutherland M.Hierarchical partitioning.The American Statistician. 1991;45:90-96.
7. Grömping U.Variable importance assessment in regression: Linear regression versus random forest.The American Statistician. 2009;63:308-319.
8. Hair E.,Halle T.,Terry-Humen E.,Lavelle B.,Calkins J.Children's school readiness in the ECLS-K: Predictions to academic, health, and social outcomes in first grade.Early Childhood Research. 2006;21:431-454.
9. Kreft I. G. G.,de Leeuw J.,Aiken L. S.The effect of different forms of centering in hierarchical linear models.Multivariate Behavioral Research. 1995;30:1-21.
10. Lindeman R. H.,Merenda P. F.,Gold R. Z.Introduction to bivariate and multivariate analysis. Glenview, IL: Scott Foresman; 1980:.
11. Lipovetsky S.,Conklin M.Analysis of regression in game theory approach.Applied Stochastic Models in Business and Industry. 2001;17:319-330.
12. Luo W.,Kwok O.Proportional reduction of prediction error in cross-classified random effects models.Sociological Methods & Research. 2010;39:188-205.
13. McCoach D. B.,Black A. C.Multilevel modeling of educational data. O'Connell A. A.McCoach D. B., ed. Charlotte, NC: Information Age Publishing; 2008:245-272.
14. Moerbeek M.The consequence of ignoring a level of nesting in multilevel analysis.Multivariate Behavioral Research. 2004;39:129-149.
15. Raudenbush S. W."Centering" predictors in multilevel analysis: Choices in consequences.Multilevel Modeling Newsletter. 1989a;1:10-12.
16. Raudenbush S. W.A response to Longord and Plewis.Multilevel Modeling Newsletter. 1989b;1:8-10.
17. Raudenbush S. W.,Bryk A. S.Hierarchical Linear Models. Applications and data analysis methods. Thousand Oaks, CA: Sage; 2002:.
18. Singer J. D.,Willett J. B.Applied longitudinal data analysis: Modeling change and event occurrence. Oxford: Oxford University Press; 2003:.
19. Snijders T.,Bosker R. J.Modeled variance in two-level models.Sociological Methods & Research. 1994;22:342-363.
20. Tranmer M.Ignoring a level in a multilevel model: Evidence from UK census data.Environment and Planning. 2001;33:941-948.
21. Van den Noortgate W.,Opdenakker M. C.,Onghena P.The effects of ignoring a level in multilevel analysis.School Effectiveness and School Improvement. 2005;16:281-303.
22. Van Landeghem G.,De Fraine B.,Van Damme J.The consequence of ignoring a level of nesting in multilevel analysis: A comment.Multivariate Behavioral Research. 2005;40:423-434.
23. Waller N. G.Fungible weights in multiple regression.Psychometika. 2008;73:691-703.