21 citations · 70 across the 11 of their papers we have counts for
12 papers
Discovery and inference of possibly bi-directional causal relationships with invalid instrumental variables
Wei Li, Rui Duan, Sai Li
Learning causal relationships between pairs of complex traits from observational studies is of great interest across various scientific domains. However, most existing methods assu…
Leveraging Local Distributions in Mendelian Randomization: Uncertain Opinions are Invalid
Ziya Xu, Sai Li
Mendelian randomization (MR) considers using genetic variants as instrumental variables (IVs) to infer causal effects in observational studies. However, the validity of causal infe…
A Focusing Framework for Testing Bi-Directional Causal Effects with GWAS Summary Data
Sai Li, Ting Ye
Mendelian randomization (MR) is a powerful method that uses genetic variants as instrumental variables (IVs) to infer the causal effect of a modifiable exposure on an outcome. Alth…
Estimation and Inference with Proxy Data and its Genetic Applications
Sai Li, T. Tony Cai, Hongzhe Li
Existing high-dimensional statistical methods are largely established for analyzing individual-level data. In this work, we study estimation and inference for high-dimensional line…
Improving Out-of-Distribution Robustness via Selective Augmentation
Huaxiu Yao, Yu Wang, Sai Li +4
Machine learning algorithms typically assume that training and test examples are drawn from the same distribution. However, distribution shift is a common problem in real-world app…
A Regression-based Approach to Robust Estimation and Inference for Genetic Covariance
Jianqiao Wang, Sai Li, Hongzhe Li
Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits, and some variants are shown to be associated with multiple comp…