Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation
Publication
, Conference
Morucci, M; Orlandi, V; Rudin, C; Roy, S; Volfovsky, A
Published in: Proceedings of Machine Learning Research
January 1, 2020
We propose a matching method for observational data that matches units with others in unit-specific, hyper-box-shaped regions of the covariate space. These regions are large enough that many matches are created for each unit and small enough that the treatment effect is roughly constant throughout. The regions are found as either the solution to a mixed integer program, or using a (fast) approximation algorithm. The result is an interpretable and tailored estimate of the causal effect for each unit.
Duke Scholars
Published In
Proceedings of Machine Learning Research
EISSN
2640-3498
Publication Date
January 1, 2020
Volume
124
Start / End Page
1089 / 1098
Citation
APA
Chicago
ICMJE
MLA
NLM
Morucci, M., Orlandi, V., Rudin, C., Roy, S., & Volfovsky, A. (2020). Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. In Proceedings of Machine Learning Research (Vol. 124, pp. 1089–1098).
Morucci, M., V. Orlandi, C. Rudin, S. Roy, and A. Volfovsky. “Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation.” In Proceedings of Machine Learning Research, 124:1089–98, 2020.
Morucci M, Orlandi V, Rudin C, Roy S, Volfovsky A. Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. In: Proceedings of Machine Learning Research. 2020. p. 1089–98.
Morucci, M., et al. “Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation.” Proceedings of Machine Learning Research, vol. 124, 2020, pp. 1089–98.
Morucci M, Orlandi V, Rudin C, Roy S, Volfovsky A. Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. Proceedings of Machine Learning Research. 2020. p. 1089–1098.
Published In
Proceedings of Machine Learning Research
EISSN
2640-3498
Publication Date
January 1, 2020
Volume
124
Start / End Page
1089 / 1098