Regression commonality analysis: A technique for quantitative theory building

Human Resource Development Review

Volumn 10, Issue 3, 2011, Pages 329-340

  Nimon, Kim ^a   Reio Jr , Thomas G ^b  

^a UNIVERSITY OF NORTH TEXAS   (United States)

^b FLORIDA INTERNATIONAL UNIVERSITY   (United States)

Author keywords

commonality analysis; human resource development; multiple regressions; quantitative theory building

Indexed keywords

EID: 80051625244     PISSN: 15344843     EISSN: 15526712     Source Type: Journal    
DOI: 10.1177/1534484311411077     Document Type: Article

References (26)

1. Capraro, R.M., & Capraro, M.M. (2001). Commonality analysis: Understanding variance contributions to overall canonical correlation effects of attitude toward mathematics on geometry achievement. Multiple Linear Regression Viewpoints, 27(2), 16-23.
2. Cohen, J., Cohen, P., West, S.G., & Aiken, L.S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah, NJ: Erlbaum.
3. Courville, T., & Thompson, B. (2001). Use of structure coefficients in published multiple regression articles: Beta is not enough. Educational and Psychological Measurement, 61, 229-248.
4. Fox, J. (1991). Regression diagnostics: An introduction. Newbury Park, CA: SAGE.
5. Frederick, B.N. (1999). Partitioning variance in the multivariate case: A step-by-step guide to canonical commonality analysis. In B. Thompson (Ed.), Advances in social science methodology (Vol. 5, pp. 305-318). StaMford, CT: JAI.
6. Huberty, C.J. (1989). Problems with stepwise methods-better alternatives. In B. Thompson (Ed.), Advances in social science methodology (Vol. 1, pp. 43-70). Greenwich, CT: JAI.
7. Lorenzo-Seva, U., Ferrando, P.J., & Chico, E. (2010). Two SPSS programs for interpreting multiple regression results. Behavior Research Methods, 42, 29-35.
8. Mayeske, G.W., Cohen, W.M., Wisler, C.E., Okada, T., Beaton, A.E., Proshek, J.M.,Tabler, K. A. (1969). A study of our nation's schools. Washington, DC: U.S. Department of Health, Education, and Welfare, Office of Education.
9. Mood, A.M. (1969). Macro-analysis of the American educational system. Operations Research, 17, 770-784.
10. Mood, A.M. (1971). Partitioning variance in multiple regression analysis as a tool for developing learning models. American Educational Research Journal, 8, 191-202.
11. Newton, R.G., & Spurrell, D.J. (1967). A development of multiple regression for the analysis of routine data. Applied Statistics, 16, 51-64.
12. Nimon, K. (2010). Regression commonality analysis: Demonstration of an SPSS Solution. Multiple Linear Regression Viewpoints, 36(1),10-17.
13. Nimon, K., Gavrilova, M., & Roberts, J.K. (2010). Regression results in human resource development research: Are we reporting enough? In C. Graham, & K. Dirani (Eds.), Proceedings of the Human Resource Development 2010 International Conference (pp. 803-812). Knoxville, TN: AHRD.
14. Nimon, K., Henson, R., & Gates, M. (2010). Revisiting interpretation of canonical correlation analysis: A tutorial and software solution for canonical commonality analysis. Multivariate Behavioral Research, 45, 702-724.
15. Nimon, K., Lewis, M., Kane, R., & Haynes, R.M. (2008). An R package to compute communality coefficients in the multiple regression case: An introduction to the package and a practical example. Behavior Research Methods, 40, 457-466.
16. Nimon, K., & Roberts, J.K. (2009). Yhat: Interpreting regression effect. R package version 1.0-3.
17. Nunnally, J.C., & Bernstein, I.H. (1994). Psychometric theory. New York, NY: McGraw-Hill.
18. Onwuegbuzie, A.J., & Daniel, L.G. (2003). Typology of analytical and interpretational errors in quantitative and qualitative educational research. Current Issues in Education, 6(2). Retrieved fromhttp://cie.ed,asu.edu/volume6/number2/.
19. Pedhazur, E.J. (1982). Multiple regression in behavioral research: Explanation and prediction (2nd ed.). New York, NY: Holt, Rinehard & Winston.
20. Pedhazur, E.J. (1997). Multiple regression in behavioral research: Explanation and prediction (3rd ed.). Ft. Worth, TX: Harcourt Brace.
21. Podsakoff, P.M., Ahearne, M., & MacKenzie, S.B. (1997). Organizational citizenship behavior and the quantity and quality of work group performance. Journal of Applied Psychology, 82, 262-270.
22. Rowell, R.K. (1991, January). Partitioning predicted variance into constituent parts: How to conduct commonality analysis (ERIC Document Reproduction Service No. ED328589). Paper presented at the annual meeting of the Southwest Educational Research Association, San Antonio, TX.
23. Siebold, D.R., & McPhee, R.D. (1979). Commonality analysis: A method for decomposing explained variance in multiple regression analysis. Human Communication Research, 5, 355-363.
24. Thompson, B. (2006). Foundations of behavioral statistics: An insight-based approach. New York, NY: Guilford.
25. Zientek, L.R., & Thompson, B. (2006). Commonality analysis: Partitioning variance to facilitate better understanding of data. Journal of Early Intervention, 28, 299-307.
26. Zientek, L.R., & Thompson, B. (2009). Matrix summaries improve research reports: Secondary analyses using published literature. Educational Researcher, 38, 343-352.