260 citations · 828 across the 46 of their papers we have counts for
63 papers
Qini Curves for Multi-Armed Treatment Rules
Erik Sverdrup, Han Wu, Susan Athey +1
Qini curves have emerged as an attractive and popular approach for evaluating the benefit of data-driven targeting rules for treatment allocation. We propose a generalization of th…
Policy Learning under Biased Sample Selection
Lihua Lei, Roshni Sahoo, Stefan Wager
Practitioners often use data from a randomized controlled trial to learn a treatment assignment policy that can be deployed on a target population. A recurring concern in doing so…
Experimenting under Stochastic Congestion
Shuangning Li, Ramesh Johari, Xu Kuang +1
We study randomized experiments in a service system when stochastic congestion can arise from temporarily limited supply or excess demand. Such congestion gives rise to cross-unit…
Learning from a Biased Sample
Roshni Sahoo, Lihua Lei, Stefan Wager
The empirical risk minimization approach to data-driven decision making requires access to training data drawn under the same conditions as those that will be faced when the decisi…
Switchback Experiments under Geometric Mixing
Yuchen Hu, Stefan Wager
The switchback is an experimental design that measures treatment effects by repeatedly turning an intervention on and off for a whole system. Switchback experiments are a robust wa…
Treatment Heterogeneity for Survival Outcomes
Yizhe Xu, Nikolaos Ignatiadis, Erik Sverdrup +3
Estimation of conditional average treatment effects (CATEs) plays an essential role in modern medicine by informing treatment decision-making at a patient level. Several metalearne…