rdlocrand: Local Randomization Methods for RD Designs

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. Under the local randomization approach, RD designs can be interpreted as randomized experiments inside a window around the cutoff. This package provides tools to perform randomization inference for RD designs under local randomization: rdrandinf() to perform hypothesis testing using randomization inference, rdwinselect() to select a window around the cutoff in which randomization is likely to hold, rdsensitivity() to assess the sensitivity of the results to different window lengths and null hypotheses and rdrbounds() to construct Rosenbaum bounds for sensitivity to unobserved confounders. See Cattaneo, Titiunik and Vazquez-Bare (2016) <https://rdpackages.github.io/references/Cattaneo-Titiunik-VazquezBare_2016_Stata.pdf> for further methodological details.

Version: 1.0
Depends: R (≥ 3.1)
Imports: AER, sandwich
Published: 2022-06-21
DOI: 10.32614/CRAN.package.rdlocrand
Author: Matias D. Cattaneo, Rocio Titiunik, Gonzalo Vazquez-Bare
Maintainer: Gonzalo Vazquez-Bare <gvazquez at econ.ucsb.edu>
License: GPL-2
NeedsCompilation: no
In views: Econometrics
CRAN checks: rdlocrand results


Reference manual: rdlocrand.pdf


Package source: rdlocrand_1.0.tar.gz
Windows binaries: r-devel: rdlocrand_1.0.zip, r-release: rdlocrand_1.0.zip, r-oldrel: rdlocrand_1.0.zip
macOS binaries: r-release (arm64): rdlocrand_1.0.tgz, r-oldrel (arm64): rdlocrand_1.0.tgz, r-release (x86_64): rdlocrand_1.0.tgz, r-oldrel (x86_64): rdlocrand_1.0.tgz
Old sources: rdlocrand archive


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