5 papers
Mendelian Randomization Methods for Causal Inference: Estimands, Identification and Inference
Minhao Yao, Anqi Wang, Xihao Li +1
Mendelian randomization (MR) has become an essential tool for causal inference in biomedical and public health research. By using genetic variants as instrumental variables, MR hel…
Semiparametric Causal Inference for Right-Censored Outcomes with Many Weak Invalid Instruments
Qiushi Bu, Wen Su, Xingqiu Zhao +1
We propose a semiparametric framework for causal inference with right-censored survival outcomes and many weak invalid instruments, motivated by Mendelian randomization in biobank…
Constructive Instrumental Variable Identification and Inference with Many Weak Interaction Moments
Di Zhang, Minhao Yao, Zhonghua Liu +1
Instrumental variable methods are widely used for causal inference, but identification becomes especially challenging when instruments are weak and potentially invalid. These chall…
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation
Qinshuo Liu, Zixin Wang, Xi-An Li +4
Semiparametric statistics play a pivotal role in a wide range of domains, including but not limited to missing data, causal inference, and transfer learning, to name a few. In many…
An Introduction to Causal Inference Methods with Multi-omics Data
Minhao Yao, Zhonghua Liu
Omics biomarkers play a pivotal role in personalized medicine by providing molecular-level insights into the etiology of diseases, guiding precise diagnostics, and facilitating tar…