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Shuangning Li
Researcher at Stanford University
Publications - 10
Citations - 45
Shuangning Li is an academic researcher from Stanford University. The author has contributed to research in topics: Causal inference & Computer science. The author has an hindex of 3, co-authored 7 publications receiving 22 citations.
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Random Graph Asymptotics for Treatment Effect Estimation under Network Interference
Shuangning Li,Stefan Wager +1 more
TL;DR: In this article, the authors consider large-sample asymptotics for treatment effect estimation under network interference in a setting where the exposure graph is a random draw from a graphon, and show that popular estimators are considerably more accurate than existing results suggest.
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Average Treatment Effects in the Presence of Interference
TL;DR: In this paper, the authors propose a definition for the average indirect effect of a binary treatment in the potential outcomes model for causal inference, analogous to the standard definition of the average direct effect, and can be expressed without needing to compare outcomes across multiple randomized experiments.
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Searching for consistent associations with a multi-environment knockoff filter
TL;DR: This article developed a method based on model-X knockoffs to find conditional associations that are consistent across diverse environments, controlling the false discovery rate in genome-wide association studies, in which consistency across populations with diverse ancestries mitigates confounding due to unmeasured variants.
Maxway CRT: Improving the Robustness of the Model-X Inference
Shuangning Li,Molei Liu +1 more
TL;DR: The MaxwayCRT is proposed, a more robust inference approach for conditional independence when the conditional distribution of X is unknown and needs to be estimated from the data, and the type-I error inflation of the Maxway CRT can be controlled by the learning error for the low-dimensional adjusting model plus the product of learning errors for the distribution ofX | Z and the Distribution of Y | Z.
Journal ArticleDOI
Sharp Bounds for Exponential Approximations of NWUE Distributions
Mark Brown,Shuangning Li +1 more
TL;DR: In this article, the authors derived sharp bounds for the Kolmogorov distance between G and the unit exponential distribution, as well as G and an exponential distribution with the same mean as G, and applied the bounds to geometric convolutions and to first passage times.