Statistical Power for Regression Discontinuity Designs in Education Evaluations

By Peter Z. Schochet. 2009

112 citations recorded by the source corpus.

Subfields: Education, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/387cad5186c24918970c7f3ce6c3b3e50df4a2f6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Education

1. Sean F. Reardon
2. John P. Robinson
3. Ann Owens
4. A. Kalil
5. Christopher Jencks
6. S. Peters
7. David M. Quinn
8. James S. Kim

In Statistics and Probability

1. John P. Robinson
2. Sean F. Reardon

Citations in the corpus

• Regression Discontinuity Designs (2021, unknown): “The implementation of these falsification analyses differs depending on whether a continuity-based or a local randomization approach is used; see, respectively, Section 5 in Cattaneo, Idrobo and Titiunik (2020) and Section 2.3 in Cattaneo, Idrobo and Titiunik (2024).”
• Regression Discontinuity Designs With Multiple Rating-Score Variables (2012, methodology): “STATISTICAL POWER OF MRSRD DESIGNS The goal with any RD design is to obtain a precise unbiased estimate of the treatment effect (Imbens & Lemieux, 2008b; Schochet, 2009); this is also true for MRSRD.”