rdrobust: Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs

Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).

Version:	3.0.0
Depends:	R (≥ 3.1.1)
Imports:	ggplot2, MASS
Published:	2025-07-19
DOI:	10.32614/CRAN.package.rdrobust
Author:	Sebastian Calonico [aut, cre], Matias D. Cattaneo [aut], Max H. Farrell [aut]
Maintainer:	Sebastian Calonico <scalonico at ucdavis.edu>
License:	GPL-3
NeedsCompilation:	no
In views:	CausalInference, Econometrics
CRAN checks:	rdrobust results

Documentation:

Reference manual:

rdrobust.html , rdrobust.pdf

Downloads:

Package source:	rdrobust_3.0.0.tar.gz
Windows binaries:	r-devel: rdrobust_3.0.0.zip, r-release: rdrobust_3.0.0.zip, r-oldrel: rdrobust_3.0.0.zip
macOS binaries:	r-release (arm64): rdrobust_3.0.0.tgz, r-oldrel (arm64): rdrobust_3.0.0.tgz, r-release (x86_64): rdrobust_3.0.0.tgz, r-oldrel (x86_64): rdrobust_3.0.0.tgz
Old sources:	rdrobust archive

Reverse dependencies:

Reverse imports:	causalQual, hdthreshold, rddtools, rdhte, rdlearn, rdmulti, rdpower, SpatialRDD
Reverse suggests:	DeclareDesign, grf, rdss

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