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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: 2.1.0
Depends: R (≥ 4.0.0)
Imports: methods, stats, ggplot2
Suggests: lme4, boot, testthat, car, covr, knitr, rmarkdown, pscl, dynlm, reshape2, betareg, performance
Published: 2024-02-05
DOI: 10.32614/CRAN.package.dominanceanalysis
Author: Claudio Bustos Navarrete ORCID iD [aut, cre, cph], Filipa Coutinho Soares ORCID iD [aut]
Maintainer: Claudio Bustos Navarrete <clbustos at gmail.com>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: dominanceanalysis results

Documentation:

Reference manual: dominanceanalysis.pdf
Vignettes: Exploring predictors' importance in binomial logistic regressions

Downloads:

Package source: dominanceanalysis_2.1.0.tar.gz
Windows binaries: r-devel: dominanceanalysis_2.1.0.zip, r-release: dominanceanalysis_2.1.0.zip, r-oldrel: dominanceanalysis_2.1.0.zip
macOS binaries: r-release (arm64): dominanceanalysis_2.1.0.tgz, r-oldrel (arm64): dominanceanalysis_2.1.0.tgz, r-release (x86_64): dominanceanalysis_2.1.0.tgz, r-oldrel (x86_64): dominanceanalysis_2.1.0.tgz
Old sources: dominanceanalysis archive

Reverse dependencies:

Reverse suggests: domir

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.