NonlinearDiD: Staggered Difference-in-Differences with Nonlinear Outcomes
Supports staggered difference-in-differences designs with
nonlinear outcomes for both panel and repeated cross-section data.
Implements estimators for staggered treatment adoption with binary,
count, and other nonlinear outcomes, extending Callaway and Sant'Anna
(2021) <doi:10.1016/j.jeconom.2020.12.001> to settings with nonlinear
outcome models such as logit, probit, and Poisson. For panel data,
units are followed over time and 'idname' identifies repeated
observations. For repeated cross-section data, observations are
independent within each time period; 'idname' is optional and may
identify survey records or households, but the estimator does not
require the same units to appear across periods. Repeated cross-section
estimation includes pooled quasi-maximum likelihood approaches motivated
by Wooldridge (2023) <doi:10.1093/ectj/utad016>, with optional weighting
and clustered inference. Methods also draw on Roth and Sant'Anna (2023)
<doi:10.3982/ECTA19402> and Sant'Anna and Zhao (2020)
<doi:10.1016/j.jeconom.2020.06.003>.
| Version: |
0.2.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
stats, utils, MASS, sandwich, lmtest, ggplot2 |
| Suggests: |
did, dplyr, knitr, rmarkdown, testthat (≥ 3.0.0), covr |
| Published: |
2026-05-20 |
| DOI: |
10.32614/CRAN.package.NonlinearDiD |
| Author: |
Subir Hait  [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: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
NonlinearDiD results |
Documentation:
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