itamuria/LRErdd: Regression Discontinuity Designs as Local Randomized Experiments

The \proglang{R} LRErdd package (Regression Discontinuity Designs as Local Randomized Experiments) includes 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 \cite{LiMatteiMealli2015}. We present the package with a case study. A subset of functions implements the design phase of the study where the focus is on the selection of suitable subpopulations for which we can draw valid causal inference. 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 LRErdd 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 RD designs. We illustrate our approach in a study concerning the effects of University grants on the dropout.

install.packages("remotes")
remotes::install_github("itamuria/LRErdd")