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.

Documentation:

Downloads:

Linking:

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