Do not adjust coefficients in Shapley value regression

Applied Stochastic Models in Business and Industry

Volumn 26, Issue 2, 2010, Pages 194-202

  Grömping, Ulrike ^a   Landau, Sabine ^b  

^a BEUTH UNIVERSITY OF APPLIED SCIENCES   (Germany)

^b KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

Lord's paradox; Multicollinearity; Multiple regression; Shapley value regression; Suppression

Indexed keywords

ALTERNATIVE PROCEDURES; MULTICOLLINEARITY; MULTIPLE REGRESSIONS; REGRESSION COEFFICIENT; RELATIVE IMPORTANCE; SHAPLEY VALUE;

GAME THEORY;

REGRESSION ANALYSIS;

EID: 77950825779     PISSN: 15241904     EISSN: 15264025     Source Type: Journal    
DOI: 10.1002/asmb.773     Document Type: Article

References (33)

1. Lipovetsky S, Conklin M. Analysis of regression in game theory approach. Applied Stochastic Models in Business and Industry 2001; 17: 319-330. DOI: 10.1002/asmb.446. (Pubitemid 34023120)
2. Conklin M, Powaga K, Lipovetsky S. Customer satisfaction analysis: identification of key drivers. European Journal of Operational Research 2004; 154: 819-827. DOI: 10.1016/S0377-2217(02)00877-9.
3. Tang J, Weiner J. Multicollinearity in CSAT studies. Proceedings of the Sawtooth Software Conference, October 2004, 83-90.
4. Ipsos Insight. It's not all about efficacy, it's about emotion: understanding what drives physicians' prescribing decisions, 2007. Available from: http://www.ipsosinsight.com/pdf/ipsoshealthwebinardeck.pdf, accessed November 21, 2008, 7: 30 pm GMT.
5. Grenville A. Emotional reactions to Prime Ministers past and present, and current party leaders, 2007. Available from: http://www.angusreidstrategies. com/uploads/pages/pdfs/EMOINDEXDEC2007.pdf, accessed November 21, 2008, 7pm GMT.
6. Mandel I. Statistical modeling and business expertise, or where is the truth? Model Assisted Statistics and Applications 2008; 3: 3-20.
7. MacLean S. Opinion: the importance of importance. Australian Market and Social Research Society. Research News, June 2008, 2008. Available from: http://www.mrsa.com.au/index.cfm?a=detail&id=2932&eid=151.
8. Lindeman RH, Merenda PF, Gold RZ. Introduction to Bivariate and Multivariate Analysis. Scott, Foresman: Glenview, IL, 1980.
9. Kruskal W. Relative importance by averaging over orderings. The American Statistician 1987; 41: 6-10.
10. Kruskal W. Correction to 'relative importance by averaging over orderings'. The American Statistician 1987; 41: 341.
11. Budescu DV. Dominance analysis: a new approach to the problem of relative importance in multiple regression. Psychological Bulletin 1993; 114: 542-551.
12. Hoffman PJ. The paramorphic representation of clinical judgment. Psychological Bulletin 1960; 57: 116-131.
13. Pratt JW. Dividing the indivisible: using simple symmetry to partition variance explained. Proceedings of Second Tampere Conference in Statistics, Pukkila T, Puntanen S (eds). University of Tampere: Finland, 1987; 245-260.
14. Thomas DR, Hughes E, Zumbo BD. On variable importance in linear regression. Social Indicators Research 1998; 45: 253-275. (Pubitemid 29083882)
15. Darlington RB. Multiple regression in psychological research and practice. Psychological Bulletin 1968; 69: 161-182.
16. Johnson JW, Lebreton JM. History use of relative importance indices in organizational research. Organizational Research Methods 2004; 7: 238-257. DOI: 10.1177/1094428104266510. (Pubitemid 38845329)
17. Grömping U. Estimators of relative importance in linear regression based on variance decomposition. The American Statistician 2007; 61: 139-147. DOI: 10.1198/000313007X188252.
18. Stufken J. On hierarchical partitioning. The American Statistician 1992; 46: 70-71.
19. Feldman B. Relative importance and value, 2005. Manuscript (Version 1.1, March 19 2005), Downloadable at http://www.prismanalytics.com/docs/ RelativeImportance050319.pdf.
20. Grömping U. Relative importance for linear regression in R: the package relaimpo. Journal of Statistical Software 2006; 17(1). URL: http://www.jstatsoft.org/v17/.
21. Tu Y-K, Gunnell D, Gilthorpe MS. Simpson's paradox, Lord's paradox, and suppression effects are the same phenomenon-the reversal paradox. Emerging Themes in Epidemiologiy 2008; 5(2):DOI: 10.1186/1742-7622-5-2. (Pubitemid 351327204)
22. Arah OA. The role of causal reasoning in understanding Simpson's paradox, Lord's paradox, and the suppression effect: covariate selection in the analysis of observational studies. Emerging Themes in Epidemiologiy 2008; 5(5). (Commentary to Tu et al. 2008). DOI: 10.1186/1742-7622-5-5. (Pubitemid 351389091)
23. R development core team. R: a language and environment for statistical computing. R foundation for Statistical computing, ISBN 3-900051-07-0, 2008, Vienna, Austria. Available from: URL: http://www.R-project.org.
24. Statlib data sets and stories library, 2008. Available from: http://lib.stat.cmu.edu/DASL/Stories/wages.html (22 June 2008).
25. Greenberg DH, Kosters M. Income Guarantees and the Working Poor. The Rand Corporation R-579-OEO, 1970.
26. Le Moual N, Kauffmann F, Eisen EA, Kennedy SM. The healthy worker effect in asthma. American Journal of Respiratory and Critical Care Medicine 2008; 177:4-10. DOI: 10.1164/rccm.200703-415PP.
27. Becklake MR, Lalloo U. The 'healthy smoker': a phenomenon of health selection? Respiration 1990; 57: 137-144.
28. Meinert R, Frischer T, Kühr J. The healthy passive smoker: relationship between bronchial hyperactivity in school children and maternal smoking. Journal of Epidemiol Community Health 1994; 48: 325-326. (Pubitemid 2091022)
29. Gourieroux C, Monfort A. Statistics and Econometric Models: Volume 2 (Testing, Confidence Regions, Model Selection, and Asymptotic Theory). Cambridge University Press: Cambridge, 1995.
30. Grömping U. The ic.infer Package (Inequality constrained inference in linear normal situations). R package version 1.0-6. R Development Core Team (2008). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing: Vienna, Austria, 2008.
31. Dorfman JH, McIntosh CS. Imposing inequality restrictions: efficiency gains from economic theory. Economic Letters 2001; 71: 205-209. (Pubitemid 33255852)
32. Judge GG, Yancey TA. Sampling properties of an inequality-restricted estimator. Economics Letters 1981; 7: 327-333.
33. Thomson M, Schmidt P. A note on the comparison of the mean square error of inequality constrained least squares and other related estimators. The Review of Economics and Statistics 1982; 64: 174-176.