Matias D. Cattaneo, Luke Keele, Rocio Titiunik
arXiv 15 Oct 2021 · Statistics — Methodology · 21 citations (OpenAlex)
arXiv:2110.08410 · PDF · DOI · OpenAlex · Extracted main text
The Regression Discontinuity (RD) design is a widely used non-experimental method for causal inference and program evaluation. While its canonical formulation only requires a score and an outcome variable, it is common in empirical work to encounter RD analyses where additional variables are used for adjustment. This practice has led to misconceptions about the role of covariate adjustment in RD analysis, from both methodological and empirical perspectives. In this chapter, we review the different roles of covariate adjustment in RD designs, and offer methodological guidance for its correct use.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Calonico, S., Cattaneo, M. D., Farrell, M. H., and Titiunik, R (2019) Regression Discontinuity Designs using Covariates self | 0.811 | 4 | 2 | 100% |
| 2 | Cattaneo, M. D., Titiunik, R., and Vazquez-Bare, G (2017) Comparing Inference Approaches for RD Designs: A Reexamination of the Effect of Head Start on Child Mortality self | 0.737 | 3 | 2 | 100% |
| 3 | Cattaneo, M. D., and Titiunik, R (2022) Regression Discontinuity Designs self | 0.737 | 3 | 2 | 100% |
| 4 | Imbens, G. W., and Rubin, D. B (2015) Causal inference in statistics, social, and biomedical sciences | 0.737 | 3 | 2 | 100% |
| 5 | Cattaneo, M. D., Idrobo, N., and Titiunik, R (2020) a) self | 0.644 | 2 | 2 | 100% |
| 6 | height .65ex depth -.6ex width 3em\ (2022) a) | 0.644 | 2 | 2 | 100% |
| 7 | Cattaneo, M. D., Keele, L., and Titiunik, R (2022) b), A Guide to Regression Discontinuity Designs in Medical Applications self | 0.644 | 2 | 2 | 100% |
| 8 | height .65ex depth -.6ex width 3em\ (2020) b), The Regression Discontinuity Design, in | 0.644 | 2 | 2 | 100% |
| 9 | Rosenbaum, P. R (2010) Design of observational studies | 0.644 | 2 | 2 | 100% |
| 10 | Angrist, J. D., and Rokkanen, M (2015) Wanna get away? Regression discontinuity estimation of exam school effects away from the cutoff | 0.511 | 2 | 1 | 100% |
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