Bio

Shu Yang is Associate Professor of Statistics at North Carolina State University. Her primary research interest is causal inference and data integration, particularly with applications to comparative effectiveness research in health studies. She also works extensively on methods for missing data and spatial statistics.

Website: https://shuyang.wordpress.ncsu.edu/

Research Impact Dashboard

Area(s) of Expertise

Causal inference in longitudinal observational data
Semiparametric efficient estimation
Missing data analysis and imputation methods

Publications

• A Robust Framework for Two-Sample Mendelian Randomization under Population Heterogeneity , arXiv (Cornell University) (2026)
• A Spectral Confounder Adjustment for Spatial Regression with Multiple Exposures and Outcomes , Journal of the American Statistical Association (2026)
• Adaptive Influence-Based Borrowing Framework for Improving Treatment Effect Estimation in RCTs Using External Controls , arXiv (Cornell University) (2026)
• Adaptive Influence-Based Borrowing Framework for Improving Treatment Effect Estimation in RCTs Using External Controls , Statistics in Biopharmaceutical Research (2026)
• Advancing Long-Term Outdoor Air Pollution Exposure Assessment for Health Studies: Lessons from a Multinational Research Initiative , Current Environmental Health Reports (2026)
• Augmented match weighted estimators: new methods for estimating average treatment effects under extreme propensity scores , Journal of Biopharmaceutical Statistics (2026)
• Bayesian Structured Mediation analysis with Unobserved confounders , Biometrics (2026)
• Externally Controlled Trials: A Review of Design and Borrowing Through a Causal Lens , arXiv (Cornell University) (2026)
• History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes , arXiv (Cornell University) (2026)
• Improving Sensitivity Analysis By Synthesizing Randomized Clinical Trials With Limited Overlap , Statistics in Medicine (2026)