martinctc/rwa: Perform a Relative Weights Analysis

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.

Getting started

Package details

AuthorMartin Chan <martinchan53@gmail.com>
MaintainerMartin Chan <martinchan53@gmail.com>
LicenseGPL-3
Version0.0.3
URL https://github.com/martinctc/rwa
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("martinctc/rwa")
martinctc/rwa documentation built on Feb. 19, 2025, 11:17 a.m.