About Anaconda Help Download Anaconda

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.

Click on a badge to see how to embed it in your web page
badge
https://anaconda.org/r/r-rwa/badges/version.svg
badge
https://anaconda.org/r/r-rwa/badges/latest_release_date.svg
badge
https://anaconda.org/r/r-rwa/badges/latest_release_relative_date.svg
badge
https://anaconda.org/r/r-rwa/badges/platforms.svg
badge
https://anaconda.org/r/r-rwa/badges/license.svg
badge
https://anaconda.org/r/r-rwa/badges/downloads.svg

© 2024 Anaconda, Inc. All Rights Reserved. (v4.0.5) Legal | Privacy Policy