78 citations · 104 across the 15 of their papers we have counts for
11 papers · 1 filter
Rerandomization under Interference
Ziang Yuan, Xinran Li, Shuangning Li
Covariates are widely used in randomized experiments to improve precision. However, in the presence of interference, where outcomes may depend on the treatment assignments of other…
Covariate Adjustment Cannot Hurt: Treatment Effect Estimation under Interference with Low-Order Outcome Interactions
Xinyi Wang, Shuangning Li
In randomized experiments, covariates are often used to reduce variance and improve the precision of treatment effect estimates. However, in many real-world settings, interference…
Optimal Targeting in Dynamic Systems
Yuchen Hu, Shuangning Li, Stefan Wager
Modern treatment targeting methods often rely on estimating a conditional average treatment effect (CATE) using machine learning tools. While effective in identifying who benefits…
Covariate Shift Corrected Conditional Randomization Test
Bowen Xu, Yiwen Huang, Chuan Hong +2
Conditional independence tests are crucial across various disciplines in determining the independence of an outcome variable from a treatment variable , conditioning on a se…
Detecting Interference in A/B Testing with Increasing Allocation
Kevin Han, Shuangning Li, Jialiang Mao +1
In the past decade, the technology industry has adopted online randomized controlled experiments (a.k.a. A/B testing) to guide product development and make business decisions. In p…
Maxway CRT: Improving the Robustness of the Model-X Inference
Shuangning Li, Molei Liu
The model-X conditional randomization test (CRT) is a flexible and powerful testing procedure for the conditional independence hypothesis: X is independent of Y conditioning on Z.…
Network Interference in Micro-Randomized Trials
Shuangning Li, Stefan Wager
The micro-randomized trial (MRT) is an experimental design that can be used to develop optimal mobile health interventions. In MRTs, interventions in the form of notifications or m…
Cooperative learning for multiview analysis
Daisy Yi Ding, Shuangning Li, Balasubramanian Narasimhan +1
We propose a new method for supervised learning with multiple sets of features ("views"). The multiview problem is especially important in biology and medicine, where "-omics" data…
Deploying the Conditional Randomization Test in High Multiplicity Problems
Shuangning Li, Emmanuel J. Candès
This paper introduces the sequential CRT, which is a variable selection procedure that combines the conditional randomization test (CRT) and Selective SeqStep+. Valid p-values are…
Searching for consistent associations with a multi-environment knockoff filter
Shuangning Li, Matteo Sesia, Yaniv Romano +2
This paper develops a method based on model-X knockoffs to find conditional associations that are consistent across diverse environments, controlling the false discovery rate. The…
Average Direct and Indirect Causal Effects under Interference
Yuchen Hu, Shuangning Li, Stefan Wager
We propose a definition for the average indirect effect of a binary treatment in the potential outcomes model for causal inference under cross-unit interference. Our definition is…