Approaches to the Estimation of the Local Average Treatment Effect in a Regression Discontinuity Design
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Publication:2835305
DOI10.1111/sjos.12224zbMath1373.62392OpenAlexW2303818082WikidataQ37418133 ScholiaQ37418133MaRDI QIDQ2835305
Aidan G. O'Keeffe, Gianluca Baio
Publication date: 2 December 2016
Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/sjos.12224
causal inferencetwo-stage least squaresregression discontinuity designlocal average treatment effect
Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Linear inference, regression (62J99)
Cites Work
- Editorial. Special issue editors' introduction: The regression discontinuity design -- theory and applications
- Regression discontinuity inference with specification error
- Randomized experiments from non-random selection in U.S. House elections
- Assumptions of IV methods for observational epidemiology
- Identification of Causal Effects Using Instrumental Variables
- Identification and Estimation of Local Average Treatment Effects
- Two-Stage Least Squares Estimation of Average Causal Effects in Models with Variable Treatment Intensity
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