Detecting heterogeneous treatment effects with instrumental variables and application to the Oregon health insurance experiment
Author:
Affiliation:
1. Department of Statistics, University of Wisconsin-Madison
2. Department of Statistics, University of Chicago
Publisher
Institute of Mathematical Statistics
Subject
Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability
Reference61 articles.
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3. Wager, S. and Athey, S. (2018). Estimation and inference of heterogeneous treatment effects using random forests. J. Amer. Statist. Assoc. 113 1228–1242.
4. Breiman, L., Friedman, J. H., Olshen, R. A. and Stone, C. J. (1984). Classification and Regression Trees. Wadsworth Statistics/Probability Series. Wadsworth Advanced Books and Software, Belmont, CA.
5. Su, X., Tsai, C.-L., Wang, H., Nickerson, D. M. and Li, B. (2009). Subgroup analysis via recursive partitioning. J. Mach. Learn. Res. 10 141–158.
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