rdrobust

Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs

Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).

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Description file content

Package
rdrobust
Type
Package
Title
Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs
Version
0.99.3
Date
2018-07-12
Author
Sebastian Calonico , Matias D. Cattaneo , Max H. Farrell , Rocio Titiunik
Maintainer
Sebastian Calonico
Description
Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).
Depends
R (>= 3.1.1)
License
GPL-2
Packaged
2018-07-12 15:37:39 UTC; SCalonico
NeedsCompilation
no
Repository
CRAN
Date/Publication
2018-07-12 16:10:03 UTC

install.packages('rdrobust')

0.99.3

10 days ago

Sebastian Calonico

GPL-2

Depends on

R (>= 3.1.1)

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