Determining Relative Importance with Independent Variable Groups: An Alternative Dominance Analysis Method
DOI:
https://doi.org/10.35566/jbds/luchmanKeywords:
Relative Importance Analysis, Dominance Analysis, Shapley Value Decomposition, Owen Value DecompositionAbstract
Grouping independent variables (IVs) in relative importance analyses like dominance analysis (DA) can reduce computation time and improve analysis feasibility. A side effect of grouping IVs is that determining the importance of individual IVs within groups is not possible. This work proposes an extension of DA where the researcher can group IVs yet still compare individual IVs. The proposed extension extends from Owen values, a variant of the Shapley value solution concept from Cooperative Game Theory. Owen values are used to generate within-group DA statistics and designations which can be used for relative importance analysis of individual IVs in IV groups. This manuscript provides an analytic example with data in the R statistical computing environment that shows how within-group DA statistics and designations are determined. The manuscript concludes by discussing how to group IVs into IV groups and potential extensions to the method to simplify the IV grouping process.
References
Antal, D. (2025). dataset: Create data frames for exchange and reuse [Computer software manual]. (R package version 0.4.1) doi: https://doi.org/10.32614/CRAN.package.dataset
Azen, R., & Budescu, D. V. (2003). The dominance analysis approach for comparing predictors in multiple regression. Psychological Methods, 8(2), 129–148. doi: https://doi.org/10.1037/1082-989X.8.2.129
Bittmann, F. (2024). A primer on dominance analysis. doi: https://doi.org/10.20944/preprints202404.1606.v1
Budescu, D. V. (1993). Dominance analysis: A new approach to the problem of relative importance of predictors in multiple regression. Psychological Bulletin, 114(3), 542–551. doi: https://doi.org/10.1037/0033-2909.114.3.542
Budescu, D. V., & Azen, R. (2004). Beyond global measures of relative importance: Some insights from dominance analysis. Organizational Research Methods, 7(3), 341–350. doi: https://doi.org/10.1177/1094428104267049
Grömping, U. (2007). Estimators of relative importance in linear regression based on variance decomposition. The American Statistician, 61(2), 139–147. doi: https://doi.org/10.1198/000313007X188252
Gu, X. (2023). Evaluating predictors’ relative importance using bayes factors in regression models. Psychological Methods, 28(4), 825–842. doi: https://doi.org/10.1037/met0000431
Johnson, J. W., & LeBreton, J. M. (2004). History and use of relative importance indices in organizational research. Organizational Research Methods, 7(3), 238–257. doi: https://doi.org/10.1177/109442810426651
Kruskal, W. (1987). Relative importance by averaging over orderings. The American Statistician, 41(1), 6–10. doi: https://doi.org/10.1080/00031305.1987.10475432
LeBreton, J. M., Tonidandel, S., & Krasikova, D. V. (2013). Residualized relative importance analysis: A technique for the comprehensive decomposition of variance in higher order regression models. Organizational Research Methods, 16(3), 449–473. doi: https://doi.org/10.1177/1094428113481065
Luchman, J. N. (2021). Determining relative importance in stata using dominance analysis: domin and domme. The Stata Journal, 21(2), 510–538. doi: https://doi.org/10.1177/1536867X211025837
Luchman, J. N. (2024). domir: Tools to support relative importance analysis [Computer software manual]. Retrieved from https://CRAN.R-project.org/package=domir (R package version 1.2.0, https://jluchman.github.io/domir/)
McLaurin, F. A., West, S. J., & Thomson, N. D. (2025). Exploring the relationship between facets of childhood trauma and violent injury risk during adulthood: A dominance analysis study. Child Abuse & Neglect, 161, 107307. doi: https://doi.org/10.1016/j.chiabu.2025.107307
Miller, B. K., Kirby, E. G., & Stevens, K. B. (2025). Dominance analysis of bright and dark dispositional predictors of socially desirable responding. Psychological Reports, 128(6), 4799–4819. doi: https://doi.org/10.1177/00332941241226908
Owen, G. (1977). Values of games with a priori unions. In Essays in mathematical economics and game theory (pp. 76–88). Springer.
Shapley, L. S. (1953). A value for n-person games. In Contributions to the theory of games II (pp. 307–317). Princeton University Press.
Thomas, D. R., Zumbo, B. D., Kwan, E., & Schweitzer, L. (2014). On Johnson’s (2000) relative weights method for assessing variable importance: A reanalysis. Multivariate Behavioral Research, 49(4), 329–338. doi: https://doi.org/10.1080/00273171.2014.905766
Tonidandel, S., & LeBreton, J. M. (2011). Relative importance analysis: A useful supplement to regression analysis. Journal of Business and Psychology, 26(1), 1–9.
Yin, K., & Zhou, L. (2025). The relative importance of peace of mind, grit, and classroom environment in predicting willingness to communicate among learners in multi-ethnic regions: a latent dominance analysis. BMC Psychology, 13(1), 1–17. doi: https://doi.org/10.1186/s40359-025-02676-2