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_0.1.0.zip, r-release:rwa_0.1.0.zip, r-oldrel:rwa_0.1.0.zip |
| macOS binaries: | r-release (arm64):rwa_0.1.0.tgz, r-oldrel (arm64):rwa_0.1.0.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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