Project Activities
The new approach will use ridge regression to obtain residuals of the outcome, with the residuals then used in a typical regression discontinuity analysis. After initial development, the researchers will extend the software to calculate standard errors in a less computationally intensive manner, to estimate treatment effect heterogeneity, and to allow for random effects at the classroom level and/or the school level.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
Opper, Isaac M., & Özek, U.. (2023). A Global Regression Discontinuity Design: Theory and Application to Grade Retention Policies. (EdWorkingPaper: 23-798). Retrieved from Annenberg Institute at Brown University: https://doi.org/10.26300/hq2t-7x64
Supplemental information
Co-Principal Investigators: Engberg, John; Johnston, William
The design of the study features simulations to compare the new technique to existing methods and an analysis of the New York City administrative data in order to provide an applied demonstration. This project will result in journal publications of the theoretical results, conference presentations, a how-to guide for the new method, and software for conducting the new method in R, Stata, and potentially Python. The research team will test the user-friendliness of the software packages on graduate students.
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
