R Observatory: Metrics for NonlinearDiD version 0.2.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

NonlinearDiD

0.2.0Package record

Staggered Difference-in-Differences with Nonlinear Outcomes

0packages depend

1.6Kdownloads / year

37.3%test coverage

13/13flavors OK

Overview

About

Maintained by Subir HaitCRAN page ↗GitHub ↗Issues ↗

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.

Changes in 0.2.0

Added support for repeated cross-section staggered DiD designs.
Added data_type = "panel" and data_type = "repeated_cross_section" options.
Made idname optional for repeated cross-section designs.
Added support for sampling weights through weightsname.
Added support for clustered inference through cluster_var.
Added examples for binary repeated cross-section outcomes with staggered treatment timing.
Preserved all panel-data functionality from version 0.1.0.

Implementation notes

Repeated cross-section ATT(g,t) uses the Wooldridge (2023) pooled QMLE with a treatment-by-period interaction. The doubly-robust variant augments this with inverse probability weighting on the estimated propensity score.

Show all changes in 0.2.0Hide the rest of the changes in 0.2.0

Sampling weights (when supplied via weightsname) are used throughout: the outcome regression, the propensity score model, and the pooled QMLE. They are multiplied with the IPW factor in the doubly-robust path.
Analytical SEs for the RCS path use sandwich::vcovCL when cluster_var is supplied, sandwich::vcovHC (HC1) otherwise. Panel SEs continue to use the influence-function approach from v0.1.0; set boot = TRUE for fully clustered panel inference.
The bootstrap automatically resamples whole clusters when cluster_var is provided, units when data_type = "panel", or individual rows when data_type = "repeated_cross_section" without clustering.
The compiled C++ helpers from v0.1.0 have been replaced with equivalent pure-R implementations, eliminating the Rcpp dependency. The package no longer requires compilation.

Bug fixes

None.

---

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("NonlinearDiD", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("causalfragility-lab/NonlinearDiD")

Development version from causalfragility-lab/NonlinearDiD. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-nonlineardid

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-NonlinearDiD

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-NonlinearDiD

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 2.7 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-09-08
ERROR12 OK, 1 ERROR2026-09-07
OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK7 OK2026-05-06

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.2.0

READMEYes · 771 wordsVignettesNoNEWSYes · 100% structured · mentions 0.2.0Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 17 (1 internal)includes a package overview page
Examples that run: 83%10 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 24%

How these are measured

Downloads

1.6K

CRAN downloads in the past year

Rank #16,283 · ~4/day · ~135/mo

Releases R versions

Daily download trend is not available in this view yet.

28530 days

76090 days

1.6K1 year

Compare downloads with other packages →

Also on129 r2u2 autocran

How downloads are counted

Repository

subirhait/NonlinearDiD ↗Account: subirhait

Moved from causalfragility-lab/nonlineardid.

2Stars

0Forks

1Open issues

0Open PRs

1Releases

12Commits

1Commit identities

12 commits · Last activity 2026-05-21 · +100% stars, 30d

Responsiveness

not measured

Stars over time

2026-07-14 · 02026-09-30 · 2

How these are measured

PracticesBeta

6 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/causalfragility-lab/nonlineardid on 2026-10-18.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Reproducibility and dev environment (2)

data-raw/Makefile

CRAN release process (1)

cran-comments.md

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

9 external dependencies (excludes base and recommended)

Installing NonlinearDiD adds 20 packages (9 with compiled code, 16 MB of source tarballs). Heaviest: ggplot2 6.0 MB, isoband 1.5 MB, sandwich 1.4 MB.

Depends (1)

R >= 4.0.0

Imports (6)

statsutilsMASSsandwich lmtest ggplot2

LinkingTo (0)

none

Suggests (6)

did dplyr knitr rmarkdown testthat covr

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (1)

Subir Hait

Author, Maintainer since 0.1.0 (2026)

Releases (2)

Pick two releases to compare their code metrics.

0.2.0Latest
record
2026-05-20 · current release · diff ↗ ·
added 1 export
sim_binary_rcs
0.1.0
record
2026-05-05
R
R 4.6.0 released · 2026-04-24

Package metadata

First published: 2026-05-05
Total releases: 2 / 1 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 4.0.0
Download size: 38 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("NonlinearDiD")

Format

Hait, S. (2026). NonlinearDiD: Staggered Difference-in-Differences with Nonlinear Outcomes (Version 0.2.0) [Computer software]. https://doi.org/10.32614/CRAN.package.NonlinearDiD

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for NonlinearDiD version 0.2.0 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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