3 papers
stat.ME2020
Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference
M. Usaid Awan, Marco Morucci, Vittorio Orlandi +3
We propose a matching method that recovers direct treatment effects from randomized experiments where units are connected in an observed network, and units that share edges can pot…
stat.ME2020
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation
Marco Morucci, Vittorio Orlandi, Sudeepa Roy +2
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…
stat.ME2019
Interpretable Almost-Matching-Exactly With Instrumental Variables
M. Usaid Awan, Yameng Liu, Marco Morucci +3
Uncertainty in the estimation of the causal effect in observational studies is often due to unmeasured confounding, i.e., the presence of unobserved covariates linking treatments a…