This article describes the R package rdrobust, which provides data-driven graphical and in ference procedures for RD designs. The package includes three main functions: rdrobust, rdbwselect and rdplot. The first function (rdrobust) implements conventional local-polynomial RD treatment effect point estimators and confidence intervals, as well as robust bias-corrected confidence intervals, for average treatment effects at the cutoff. This function covers sharp RD, sharp kink RD, fuzzy RD and fuzzy kink RD designs, among other possibilities. The second function (rdbwselect) implements several bandwidth selectors proposed in the RD literature. The third function (rdplot) provides data-driven optimal choices of evenly-spaced and quantile-spaced partition sizes, which are used to implement several data-driven RD plots.
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For attribution, please cite this work as
Calonico, et al., "The R Journal: rdrobust: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs", The R Journal, 2015
BibTeX citation
@article{RJ-2015-004,
author = {Calonico, Sebastian and Cattaneo, Matias D. and Titiunik, Rocío},
title = {The R Journal: rdrobust: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs},
journal = {The R Journal},
year = {2015},
note = {https://doi.org/10.32614/RJ-2015-004},
doi = {10.32614/RJ-2015-004},
volume = {7},
issue = {1},
issn = {2073-4859},
pages = {38-51}
}