Staggered Difference-in-Differences with Nonlinear Outcomes R package NonlinearDiD version 0.2.0 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>. Software Depends: R (>= 4.0.0) Imports: stats, utils, MASS, sandwich, lmtest, ggplot2 Suggests: did, dplyr, knitr, rmarkdown, testthat (>= 3.0.0), covr Subir Hait <haitsubi@msu.edu> Comprehensive R Archive Network (CRAN) Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>) MIT + file LICENSE (https://CRAN.R-project.org/package=NonlinearDiD/LICENSE) 2026-05-20 application/tgz https://CRAN.R-project.org/package=NonlinearDiD doi:10.32614/CRAN.package.NonlinearDiD