7 citations · 10 across the 6 of their papers we have counts for
6 papers
High-dimensional Feature Screening for Nonlinear Associations With Survival Outcome Using Restricted Mean Survival Time
Yaxian Chen, KF Lam, Zhonghua Liu
Feature screening is an important tool in analyzing ultrahigh-dimensional data, particularly in the field of Omics and oncology studies. However, most attention has been focused on…
Semiparametric Efficient G-estimation with Invalid Instrumental Variables
Baoluo Sun, Zhonghua Liu, Eric Tchetgen Tchetgen
The instrumental variable method is widely used in the health and social sciences for identification and estimation of causal effects in the presence of potentially unmeasured conf…
GENIUS-MAWII: For Robust Mendelian Randomization with Many Weak Invalid Instruments
Ting Ye, Zhonghua Liu, Baoluo Sun +1
Mendelian randomization (MR) has become a popular approach to study causal effects by using genetic variants as instrumental variables. We propose a new MR method, GENIUS-MAWII, wh…
An Eigenvalue Ratio Approach to Inferring Population Structure from Whole Genome Sequencing Data
Yuyang Xu, Zhonghua Liu, Jianfeng Yao
Inference of population structure from genetic data plays an important role in population and medical genetics studies. With the advancement and decreasing cost of sequencing techn…
A Two-Sample Robust Bayesian Mendelian Randomization Method Accounting for Linkage Disequilibrium and Idiosyncratic Pleiotropy with Applications to the COVID-19 Outcome
Anqi Wang, Zhonghua Liu
Mendelian randomization (MR) is a statistical method exploiting genetic variants as instrumental variables to estimate the causal effect of modifiable risk factors on an outcome of…
A Geometric Perspective on the Power of Principal Component Association Tests in Multiple Phenotype Studies
Zhonghua Liu, Xihong Lin
Joint analysis of multiple phenotypes can increase statistical power in genetic association studies. Principal component analysis, as a popular dimension reduction method, especial…