Perform a Relative Weights Analysis R package rwa version 0.1.1 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. Software Imports: dplyr, magrittr, stats, tidyr, ggplot2, boot, purrr, utils Suggests: knitr, rmarkdown, testthat (>= 3.0.0), rlang, spelling Martin Chan <martinchan53@gmail.com> Comprehensive R Archive Network (CRAN) Martin Chan [aut, cre] GPL-3 2026-01-20 application/tgz https://CRAN.R-project.org/package=rwa doi:10.32614/CRAN.package.rwa en-US