Estimation, Inference, and Design in Partially Nested Regression Discontinuity Studies

• In Event: Innovations in Experimental Design and Causal Inference

Abstract

We advance regression discontinuity designs for partially nested structures by formulating models, developing principles of estimation, sampling variability and inference as well as expressions to estimate the statistical power to detect main effects. The results provide a set of models, expressions, and software tools intended to inform and guide researchers in planning and analyzing studies with partially nested regression discontinuity designs.

Authors

• Benjamin Kelcey, University of Cincinnati

• Yanli Xie, Florida State University

• Fangxing Bai, University of Cincinnati