Rddtools is a new r package under development, designed to offer a set of tools to run all the. It is one of the most credible quasiexperimental research designs for identi. The analysis of the regressiondiscontinuity design in r request. R linear regression regression analysis is a very widely used statistical tool to establish a relationship model between two variables. The analysis of the regressiondiscontinuity design in r article in journal of educational and behavioral statistics 423 november 2016 with 998 reads how we measure reads. An application to the study of party advantages in the u. Rdestimate supports both sharp and fuzzy rdd utilizing the aer package for 2sls regression under the fuzzy design. Estimation is accomplished using local linear regression. We can select similar control groups using matching or controlling what economists call selection on observables we can use a treated group at a different time as its own control group with fixed effects. A provided function will utilize imbenskalyanaraman optimal bandwidth calculation.
Provides the tools to undertake estimation in regression discontinuity designs. The main new features of this upgraded version are as follows. Rd plots, estimation, inference, and extrapolation with multiple cutoffs and multiple scores. A practical introduction to regression discontinuity. The analysis of the regressiondiscontinuity design in r. In the rd design, all units have a score, and a treatment is assigned to those units whose value of the score exceeds a. Mosek is a commercial interior point solver that needs to be installed separately, while quadprog is a standard r optimization library. Regression discontinuity rd analysis is a rigorous nonexperimental1 approach that can be used to estimate program impacts in situations in which candidates are selected for treatment based on whether their value for a numeric rating exceeds a designated threshold or cutpoint. Does a discontinuity occur in the regression at the cutoff point. Weve been going over ways in which we can use control groups to isolate causal effects. An r package for robust nonparametric inference in regressiondiscontinuity designs. Covariates are problematic for inclusion in the regression discontinuity design. We will make use of the tidyverse verb mutate and pipe operators from the magrittr package to create d. Randomization inference in the regression discontinuity design.