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LRErdd  

Regression Discontinuity Designs as Local Randomized Experiments
View on CRAN: Click here


Download and install LRErdd package within the R console
Install from CRAN:
install.packages("LRErdd")

Install from Github:
library("remotes")
install_github("cran/LRErdd")

Install by package version:
library("remotes")
install_version("LRErdd", "0.1.0")



Attach the package and use:
library("LRErdd")
Maintained by
Ibon Tamayo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-06
Latest Update: 2026-08-06
Description:
A set of functions for the design and analysis of Regression Discontinuity Designs as local randomized experiments within the potential outcome approach as formalized in Li, Mattei and Mealli (2015) <doi:10.1214/15-AOAS809>. A subset of functions implements the design phase of the study, where the focus is on the selection of suitable subpopulations for which valid causal inference can be drawn. These functions provide summary statistics of pre- and post-treatment variables by treatment status and select suitable subpopulations around the threshold where pre-treatment variables are well balanced between treatment groups, using randomization-based tests with adjustment for multiplicities. Functions for a visual inspection of the results are also provided. Finally, the package includes a set of functions for drawing inference on causal effects for the selected subpopulations using randomization-based modes of inference. Specifically, the Fisher Exact p-value and Neyman approaches are implemented for the analysis of both sharp and fuzzy Regression Discontinuity designs. The approach is illustrated in a study concerning the effects of university grants on student dropout.
How to cite:
Ibon Tamayo (2026). LRErdd: Regression Discontinuity Designs as Local Randomized Experiments. R package version 0.1.0, https://cran.r-project.org/web/packages/LRErdd. Accessed 13 Oct. 2026.
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