rdpower-package: rdpower: Power and Sample Size Calculations for RD Designs

In rdpower: Power, Sample Size, and Minimum Detectable Effect Calculations for RD Designs

rdpower: Power and Sample Size Calculations for RD Designs

Description

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. The 'rdpower' package provides tools to perform power, sample size and MDE calculations in RD designs: rdpower() calculates the power of an RD design, rdsampsi() calculates the required sample size to achieve a desired power and rdmde() calculates minimum detectable effects. This package relies on the rdrobust package. See Calonico, Cattaneo and Titiunik (2014, 2015) and Calonico, Cattaneo, Farrell and Titiunik (2017). For more details, and related Stata and R packages useful for analysis of RD designs, visit https://rdpackages.github.io/.

Author(s)

Matias D. Cattaneo, Princeton University. [e-mail]

Rocio Titiunik, Princeton University. [e-mail]

Gonzalo Vazquez-Bare, UC Santa Barbara. [e-mail]

References

Calonico, S., M. D. Cattaneo, M. Farrell and R. Titiunik. (2017). rdrobust: Software for Regression Discontinuity Designs. Stata Journal 17(2): 372-404.

Calonico, S., M. D. Cattaneo, and R. Titiunik. (2014). Robust Data-Driven Inference in the Regression-Discontinuity Design. Stata Journal 14(4): 909-946.

Calonico, S., M. D. Cattaneo, and R. Titiunik. (2015). rdrobust: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs. R Journal 7(1): 38-51.

Cattaneo, M. D., R. Titiunik and G. Vazquez-Bare. (2019). Power Calculations for Regression Discontinuity Designs. Stata Journal, 19(1): 210-245.

rdpower documentation built on May 18, 2026, 1:07 a.m.