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causalWins: Compute the Causal Win Ratio Using Nearest Neighbor Matching

Based on “Rethinking the Win Ratio: A Causal Framework for Hierarchical Outcome Analysis” (M. Even and J. Josse, 2025), this package provides implementations of three approaches - nearest neighbor matching, distributional regression forests, and efficient influence functions - to estimate the causal win ratio, win proportion, and net benefit.

Version: 0.1.0
Imports: drf, FactoMineR, grf, MatchIt
Suggests: knitr, rmarkdown, WINS, MASS
Published: 2026-04-21
DOI: 10.32614/CRAN.package.causalWins
Author: Francisco Andrade [aut], Mathieu Even [aut, cre], Julie Josse [aut]
Maintainer: Mathieu Even <mathieu.even at inria.fr>
License: AGPL (≥ 3)
NeedsCompilation: no
Materials: README
CRAN checks: causalWins results

Documentation:

Reference manual: causalWins.html , causalWins.pdf
Vignettes: A Causal Framework for Hierarchical Outcome Analysis (source, R code)

Downloads:

Package source: causalWins_0.1.0.tar.gz
Windows binaries: r-release: causalWins_0.1.0.zip, r-oldrel: causalWins_0.1.0.zip
macOS binaries: r-release (arm64): causalWins_0.1.0.tgz, r-oldrel (arm64): causalWins_0.1.0.tgz, r-release (x86_64): causalWins_0.1.0.tgz, r-oldrel (x86_64): causalWins_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=causalWins to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.