The Tabu search procedure: An alternative to the variable selection methods

Multivariate Behavioral Research

Volumn 40, Issue 3, 2005, Pages 351-371

  Mills, Jamie D ^a,d   Olejnik, Stephen F ^b   Marcoulides, George A ^c  

^a UNIVERSITY OF ALABAMA   (United States)

^b UNIVERSITY OF GEORGIA   (United States)

^c CALIFORNIA STATE UNIVERSITY   (United States)

^d UNIVERSITY OF ALABAMA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33644992769     PISSN: 00273171     EISSN: None     Source Type: Journal    
DOI: 10.1207/s15327906mbr4003_4     Document Type: Article

References (40)

1. Abramowitz, M., & Stegun, I. A. (1968). Handbook of mathematical functions (Applied Mathematics Series, 55, Seventh printing). Washington, DC: National Bureau of Standards.
2. Agresti, A. (1996). An introduction to categorical data analysis. New York: Wiley.
3. Altman, D. G., & Andersen, P. K. (1989). Bootstrap investigation of the stability of a Cox regression model. Statistics in Medicine, 8, 771-783.
4. rd ed.). Minneapolis/St. Paul, MN: West Publishing.
5. Cliff, N. (1987). Analyzing multivariate data. San Diego, CA: Harcourt Jovanovich.
6. nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
7. Derksen, S., & Keselman, H. J. (1992). Backward, forward and stepwise automated subset selection algorithms: Frequency of obtaining authentic and noise variables. British Journal of Mathematical and Statistical Psychology, 45, 265-282.
8. Drezner, Z., Marcoulides, G. A., & Salhi, S. (1998, April). Tabu search model selection procedures. Paper presented at the Annual Meeting of the Western Decision Sciences Institute, Reno, NV.
9. Drezner, Z., Marcoulides, G. A., & Salhi, S. (1999). Tabu search model selection in multiple regression analysis. Communications in Statistics, 28, 349-367.
10. Ezekiel, M. (1930). Methods of correlational analysis. New York: Wiley.
11. Flack, V. F., & Chang, P. C. (1987). Frequency of selecting noise variables in subset regression analysis: A simulation study. The American Statistician, 41, 84-86.
12. p-statistic. The Statistician, 45, 49-56.
13. Glover, F. (1986). Future paths for integer programming and links to artificial intelligence. Computers and Operations Research, 13, 533-549.
14. Gordon, H. R. D. (2001). American vocational education research association members' perceptions of statistical significance tests and other statistical controversies. Journal of Vocational Education Research, 26, 244-271.
15. Henderson, A. D., & Denison, D. R. (1989). Stepwise regression in social and psychological research. Psychological Reports, 64, 251-257.
16. Huberty, C. J. (1989). Problems with stepwise methods-better alternatives. Advances in Social Science Methodology, 1, 43-70.
17. Huberty, C. J. (1994). Applied discriminant analysis. New York: Wiley.
18. Kaiser, H. F., & Dickman, K. (1962). Sample and population score matrices and sample correlation matrices form an arbitrary population correlation matrix. Psychometrika, 45, 465-471.
19. Knapp, T. R., & Sawilowsky, S.S. (2001). Constructive criticisms of methodological and editorial practices. The Journal of Experimental Education, 70, 65-79.
20. Lomax, R. G. (2001). An introduction to statistical concepts for education and behavioral sciences. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
21. Lovell, M. C. (1983). Data mining. The Review of Economics and Statistics, 65, 1-12.
22. Mallows, C. P. (1966). Choosing a subset regression. Paper presented at the Joint Statistical Meetings of the American Statistical Association, Los Angeles, CA.
23. Marcoulides, G. A., & Drezner, Z. (2001). Specification searches in structural equation modeling with a genetic algorithm. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advanced structural equation modeling: New developments and techniques (pp. 247-268). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
24. Marcoulides, G. A., & Drezner, Z. (2003). Model specification searches using ant colony optimization algorithms. Structural Equation Modeling, 10, 154-164.
25. Marcoulides, G. A., Drezner, Z., & Schumacker, R. E. (1998). Model specification searches in structural equation modeling using Tabu search. Structural Equation Modeling, 5, 365-376.
26. McIntyre, S. H., Montgomery, D. B., Srinivasan, V., & Weitz, B. (1983). Evaluating the statistical significance of models developed by stepwise regression. Journal of Marketing Research, 20, 1-11.
27. p for model selection from all possible regressions. The Journal of Experimental Education, 68, 365-380.
28. Osman, I. H., & Laporte, G. (1996). Metaheuristics: A bibliography. Annals of Operations Research, 63, 513-623.
29. rd ed.). Fort Worth, TX: Harcourt.
30. Reeves, C. R. (1993). Modern heuristic techniques for combinatorial problems. London: Blackwell Scientific.
31. Salhi, S. (1998). Heuristic search methods. In G. A. Marcoulides (Ed.), Modern methods for business research. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
32. SAS. (2001). SAS/IML, Version 8.1 (Computer software]. Cary, NC: Author.
33. Schumacker, R. E. (1994, January). A comparison of best model selection criteria in multiple regression. Paper presented at the annual meeting of the Southwest Educational Research Association, San Antonio, TX. (ERIC Document Reproduction Service No. ED 368 787)
34. Snyder, P. (1991). Three reasons why stepwise regression methods should not be used by researchers. In B. Thompson (Ed.), Advances in educational research: Substantive findings, methodological developments (Vol. 1, pp. 99-105). Greenwich, CT: JAI
35. Thompson, B. (1989). Why won't stepwise methods die? Measurement and Evaluation in Counseling and Development, 21, 146-148.
36. Thompson, B. (1995). Stepwise regression and stepwise discriminant analysis need not apply here: A guidelines editorial. Educational and Psychological Measurement, 55, 525-534.
37. Thompson, B. (2001). Significance, effect sizes, stepwise methods, and other issues: Strong arguments move the field. The Journal of Experimental Education, 70, 80-93.
38. Wherry, R. J. (1931). A new formula for predicting the shrinkage of the coefficient of multiple correlation coefficient. Annals of Mathematical Statistics, 2, 440-451.
39. Wilkinson, L. (1979). Tests of significance in stepwise regression. Psychological Bulletin, 86, 168-174.
40. p statistic and model selection in multiple linear regression. Journal of the Market Research Society, 34, 163-172.