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NonlinearDiD: Staggered Difference-in-Differences with Nonlinear Outcomes

Implements difference-in-differences estimators for staggered treatment adoption with binary, count, and other nonlinear outcomes. Extends Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001> to handle the fundamental identification challenges that arise with nonlinear outcome models (logit, probit, Poisson) in heterogeneous treatment timing designs. Provides group-time average treatment effects on the treated (ATT), aggregation schemes, and pre-treatment parallel trends tests appropriate for nonlinear settings. Methods include doubly-robust semiparametric estimators, nonparametric bounds, and an odds-ratio DiD approach for binary outcomes. Methods extend Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>, Roth and Sant'Anna (2023) <doi:10.3982/ECTA19255>, and Wooldridge (2023) <doi:10.1093/ectj/utad016>.

Version: 0.1.0
Depends: R (≥ 4.0.0)
Imports: stats, utils, MASS, sandwich, lmtest, ggplot2, Rcpp (≥ 1.0.0)
LinkingTo: Rcpp
Suggests: did, dplyr, knitr, rmarkdown, testthat (≥ 3.0.0), covr
Published: 2026-05-05
DOI: 10.32614/CRAN.package.NonlinearDiD
Author: Subir Hait ORCID iD [aut, cre]
Maintainer: Subir Hait <haitsubi at msu.edu>
BugReports: https://github.com/causalfragility-lab/NonlinearDiD/issues
License: MIT + file LICENSE
URL: https://github.com/causalfragility-lab/NonlinearDiD
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: NonlinearDiD results

Documentation:

Reference manual: NonlinearDiD.html , NonlinearDiD.pdf
Vignettes: Functional Form Sensitivity in Nonlinear DiD (source, R code)
Staggered DiD with Nonlinear Outcomes (source, R code)

Downloads:

Package source: NonlinearDiD_0.1.0.tar.gz
Windows binaries: r-devel: NonlinearDiD_0.1.0.zip, r-release: NonlinearDiD_0.1.0.zip, r-oldrel: NonlinearDiD_0.1.0.zip
macOS binaries: r-release (arm64): NonlinearDiD_0.1.0.tgz, r-oldrel (arm64): NonlinearDiD_0.1.0.tgz, r-release (x86_64): NonlinearDiD_0.1.0.tgz, r-oldrel (x86_64): NonlinearDiD_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=NonlinearDiD 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.
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