Perform a Relative Weights Analysis (RWA) (a.k.a. Key Drivers Analysis) as per the method described in Tonidandel & LeBreton (2015) <doi:10.1007/s10869-014-9351-z>, with its original roots in Johnson (2000) <doi:10.1207/S15327906MBR3501_1>. In essence, RWA decomposes the total variance predicted in a regression model into weights that accurately reflect the proportional contribution of the predictor variables, which addresses the issue of multi-collinearity. In typical scenarios, RWA returns similar results to Shapley regression, but with a significant advantage on computational performance.
Version: | 0.1.0 |
Imports: | dplyr, magrittr, stats, tidyr, ggplot2, boot, purrr, utils |
Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0), rlang, spelling |
Published: | 2025-07-16 |
DOI: | 10.32614/CRAN.package.rwa |
Author: | Martin Chan [aut, cre] |
Maintainer: | Martin Chan <martinchan53 at gmail.com> |
BugReports: | https://github.com/martinctc/rwa/issues |
License: | GPL-3 |
URL: | https://martinctc.github.io/rwa/, https://github.com/martinctc/rwa |
NeedsCompilation: | no |
Language: | en-US |
Materials: | README NEWS |
CRAN checks: | rwa results |
Package source: | rwa_0.1.0.tar.gz |
Windows binaries: | r-devel: rwa_0.0.3.zip, r-release: rwa_0.0.3.zip, r-oldrel: rwa_0.0.3.zip |
macOS binaries: | r-release (arm64): rwa_0.0.3.tgz, r-oldrel (arm64): rwa_0.0.3.tgz, r-release (x86_64): rwa_0.1.0.tgz, r-oldrel (x86_64): rwa_0.1.0.tgz |
Old sources: | rwa archive |
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