dominanceanalysis: Dominance Analysis

Dominance analysis is a method that allows to compare the relative importance of predictors in multiple regression models: ordinary least squares, generalized linear models, hierarchical linear models, beta regression and dynamic linear models. The main principles and methods of dominance analysis are described in Budescu, D. V. (1993) <doi:10.1037/0033-2909.114.3.542> and Azen, R., & Budescu, D. V. (2003) <doi:10.1037/1082-989X.8.2.129> for ordinary least squares regression. Subsequently, the extensions for multivariate regression, logistic regression and hierarchical linear models were described in Azen, R., & Budescu, D. V. (2006) <doi:10.3102/10769986031002157>, Azen, R., & Traxel, N. (2009) <doi:10.3102/1076998609332754> and Luo, W., & Azen, R. (2013) <doi:10.3102/1076998612458319>, respectively.

Version: 1.3.0
Depends: R (≥ 3.5.0)
Imports: methods, stats
Suggests: lme4, boot, testthat, car, covr, knitr, rmarkdown, pscl, dynlm, ggplot2, reshape2, betareg
Published: 2020-01-08
Author: Claudio Bustos Navarrete ORCID iD [aut, cre], Filipa Coutinho Soares ORCID iD [aut]
Maintainer: Claudio Bustos Navarrete <clbustos at>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: dominanceanalysis results


Reference manual: dominanceanalysis.pdf
Vignettes: Exploring predictors' importance in binomial logistic regressions
Package source: dominanceanalysis_1.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: dominanceanalysis_1.3.0.tgz, r-oldrel: dominanceanalysis_1.3.0.tgz
Old sources: dominanceanalysis archive


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