causalQual: Causal Inference for Qualitative Outcomes

Implements the framework introduced in Di Francesco and Mellace (2025) <doi:10.48550/arXiv.2502.11691>, shifting the focus to well-defined and interpretable estimands that quantify how treatment affects the probability distribution over outcome categories. It supports selection-on-observables, instrumental variables, regression discontinuity, and difference-in-differences designs.

Version:	1.0.0
Imports:	AER, caret, cli, ggplot2, ggsci, grf, lmtest, magrittr, ocf, rdrobust, sandwich, stats, stringr
Suggests:	knitr, rmarkdown
Published:	2025-02-24
DOI:	10.32614/CRAN.package.causalQual
Author:	Riccardo Di Francesco [aut, cre, cph]
Maintainer:	Riccardo Di Francesco <difrancesco.riccardo96 at gmail.com>
License:	MIT + file LICENSE
URL:	https://riccardo-df.github.io/causalQual/
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	causalQual results

Documentation:

Reference manual:	causalQual.html , causalQual.pdf
Vignettes:	Introduction to causalQual (source, R code)

Downloads:

Package source:	causalQual_1.0.0.tar.gz
Windows binaries:	r-devel: causalQual_1.0.0.zip, r-release: causalQual_1.0.0.zip, r-oldrel: causalQual_1.0.0.zip
macOS binaries:	r-release (arm64): causalQual_1.0.0.tgz, r-oldrel (arm64): causalQual_1.0.0.tgz, r-release (x86_64): causalQual_1.0.0.tgz, r-oldrel (x86_64): causalQual_1.0.0.tgz

Linking:

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