Preprints
Yuhan Qian, Yifan Yi, Jun Shao, Yanyao Yi, Nicole Mayer-Hamblett, Patrick J. Heagerty, Ting Ye (2024+). From Estimands to Robust Inference of Treatment Effects in Platform Trials.
Xiaoyu Qiu, Yuhan Qian, Jaehwan Yi, Jinqiu Wang, Yu Du, Yanyao Yi, Ting Ye (2024+). Clarifying the Role of the Mantel-Haenszel Risk Difference Estimator in Randomized Clinical Trials.
Jiren Sun, Tuo Wang, Yanyao Yi, Ting Ye, Jun Shao, Yu Du (2024+). Improve the Precision of Area Under the Curve Estimation for Recurrent Events Through Covariate Adjustment.
Kan Chen, Ting Ye, Dylan S. Small (2024+). Sensitivity Analysis for Attributable Effects in Case2 studies.
Tianyu Pan, Xiang Zhang, Weining Shen, Ting Ye (2024+). A Bayesian Approach for Selecting Relevant External Data (BASE): Application to a Study of Long-Term Outcomes in a Hemophilia Gene Therapy Trial.
Yinxiang Wu, Hyunseung Kang, Ting Ye (2024+). A More Credible Approach to Multivariable Mendelian Randomization.
Marlena S. Bannick, Jun Shao, Jingyi Liu, Yu Du, Yanyao Yi, Ting Ye (2023+). A General Form of Covariate Adjustment in Randomized Clinical Trials.
2024 ASA Biopharmaceutical Section Student Paper Award
Ting Ye, Qijia He, Shuxiao Chen, Bo Zhang. The Role of Placebo Samples in Observational Studies. [Slides]
Shuxiao Chen, Bo Zhang, Ting Ye. Minimax Rates and Adaptivity in Combining Experimental and Observational Data. [Slides]
2024
Ting Ye, Kan Chen, Dylan S. Small (2024). Combining Broad and Narrow Case Definitions in Matched Case-Control Studies: Firearms in the Home and Suicide Risk. Journal of the American Statistical Association. [R package]
Tat-Thang Vo, Ting Ye, Ashkan Ertefaie, Samrat Roy, James Flory, Sean Hennessy, Stijn Vansteelandt, Dylan S. Small (2024). Structural Mean Models for Instrumented Difference-in-Differences. Electronic Journal of Statistics.
Chang Chen, Jiayao Zhang, Ting Ye, Dan Roth, Bo Zhang (2024). Causal Inference with Textual Data: A Quasi-Experimental Design Assessing the Association Between Author Metadata and Acceptance Among ICLR Submissions from 2017 to 2022. Journal of Causal Inference.
Sai Li, Ting Ye (2024). A Focusing Framework for Testing Bi-Directional Causal Effects with GWAS Summary Data. Journal of the Royal Statistical Society: Series B.
Yilin Song, James P. Hughes, Ting Ye (2024). Adjusting for Incomplete Baseline Covariates in Randomized Controlled Trials: A Cross-World Imputation Framework. Biometrics.
Jenna van Draanen, James Peng, Ting Ye, Emily C. Williams, Heather D. Hill, Ali Rowhani-Rahbar (2024). No Change in Substance Use Disorders or Overdose After Implementation of State Earned Income Tax Credit (EITC). Drug and Alcohol Dependence.
Jessica I. Lundin, Ulrike Peters, ..., Ting Ye, Wei Zhao, Laura M. Raffield, Charles Kooperberg, and On Behalf of the PAGE Study (2024). Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations. Epigenetics.
Danni Shi and Ting Ye (2024). Behavioral Carry-Over Effect and Power Consideration in Crossover Trials. Biometrics.
Katarzyna Reluga, Ting Ye, Qingyuan Zhao (2024). A Unified Analysis of Regression Adjustment in Randomized Experiments. Electronic Journal of Statistics.
Ting Ye, Zhonghua Liu, Baoluo Sun, Eric J. Tchetgen Tchetgen (2024). GENIUS-MAWII: For Robust Mendelian Randomization with Many Weak Invalid Instruments. Journal of the Royal Statistical Society: Series B. [Slides, R package]
Ting Ye, Ted Westling, Lindsay Page, Luke Keele (2024). Nonparametric Identification of Causal Effects in Clustered Observational Studies with Differential Selection. Journal of the Royal Statistical Society: Series A. [Featured at the 2024 RSS Conference]
2023
Ting Ye (2023). Book Review "Fundamentals of Causal Inference: with R, by Babette A. Brumback." Journal of the American Statistical Association.
Yuzhen Mao, Zhun Deng, Huaxiu Yao, Ting Ye, Kenji Kawaguchi, James Zou (2023). Last-Layer Fairness Fine-Tuning is Simple and Effective for Neural Networks. ICML 2023 Workshop.
Yilin Song, Ting Ye, Lewis R. Roberts, Nicholas B. Larson, Stacey J. Winham (2023). Mendelian Randomization in Hepatology: A Review of Principles, Opportunities, and Challenges. Hepatology.
Ting Ye, Jun Shao, Yanyao Yi (2023). Log-rank and stratified log-rank tests. Statistical Theory and Related Fields.
Yanyao Yi, Ying Zhang, Yu Du, Ting Ye (2023). Testing for Treatment Effect Twice Using Internal and External Controls in Clinical Trials. Journal of Causal Inference.
Ting Ye, Luke Keele, Raiden Hasegawa, Dylan S. Small (2023+). A Negative Correlation Strategy for Bracketing in Difference-in-Differences. Journal of the American Statistical Association. [Slides, R package]
Ting Ye, Jun Shao, Yanyao Yi (2023+). Covariate-Adjusted Log-Rank Test: Guaranteed Efficiency Gain and Universal Applicability. Biometrika. [Slides, Video]
Peter Ch'en, Laura Gold, Qiongshi Lu, Ting Ye, James Andrews, Payal Patel (2023). Exploring Risk Factors for Persistent Neurocognitive Sequelae after Hospitalization for COVID-19. Annals of Clinical and Translational Neurology.
Samrat Roy, Ting Ye, Ashkan Ertefaie, Tat-Thang Vo, James Flory, Sean Hennessy, Dylan S. Small (2023). Group Sequential Testing under Instrumented Difference-in-Differences approach. Statistics in Medicine.
Michelle Li, Dylan S. Small, Ting Ye, Yuzhou Lin, Daniel Webster (2023). Examining a Hypothesized Causal Chain for the Effects of the 2007 Repeal of the Permit-to-Purchase Licensing Law in Missouri: Homicide Guns Recovered in State and Within a Year of Purchase. Journal of Urban Health.
Ting Ye, Marlena Bannick, Yanyao Yi, Jun Shao (2023). Robust Variance Estimation for Covariate-Adjusted Unconditional Treatment Effect in Randomized Clinical Trials with Binary Outcomes. Statistical Theory and Related Fields. [R package]
Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou (2023). FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. ICLR.
Zhonghua Liu, Ting Ye, Baoluo Sun , Mary Schooling, and Eric J. Tchetgen Tchetgen (2023+). On Mendelian Randomization Mixed-Scale Treatment Effect Robust Identification (MR MiSTERI) and Estimation for Causal Inference. Biometrics.
Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy, Dylan S. Small (2023). Instrumented Difference-in-Differences (with discussions). Biometrics.[Slides, R package]
Baoluo Sun and Ting Ye (2023). Semiparametric Causal Mediation with Unmeasured Mediator-Outcome Confounding. Statistica Sinica.
Bo Zhang, Siyu Heng, Ting Ye, Dylan S. Small (2023). Social Distancing and COVID-19: A Randomization Inference for Structured Dose-Response Relationship. Annals of Applied Statistics.
2022
Ting Ye, Jun Shao, Yanyao Yi, Qingyuan Zhao (2022+). Toward Better Practice of Covariate Adjustment in Analyzing Randomized Clinical Trials. Journal of the American Statistical Association. [Slides, R package]
David Richardson, Ting Ye, Eric J. Tchetgen Tchetgen (2022). Generalized Difference-in-Differences. Epidemiology.
Ting Ye, Dylan S. Small, Paul R. Rosenbaum (2022). Dimensions, Power and Factors in an Observational Study of Behavior Problems After Physical Abuse of Children. Annals of Applied Statistics.
Ting Ye, Yanyao Yi, Jun Shao (2022). Inference on Average Treatment Effect under Minimization and Other Covariate-Adaptive Randomization Methods. Biometrika. [R package]
Rajiv Rao, Ting Ye, Brianna Butera (2022). The Prosodic Expression of Sarcasm vs. Sincerity by Heritage Speakers of Spanish. Languages.
2021
Jun Shao, Ting Ye, Qingyuan Zhao (2021). Comment on FDA draft guidance for industry FDA-2019-D-0934: adjusting for covariates in randomized clinical trials for drugs and biological products.
Bo Zhang, Siyu Heng, Emily J. MacKay, Ting Ye (2021). Bridging preference-based instrumental variable studies and cluster-randomized encouragement experiments: study design, noncompliance, and average cluster effect ratio. Biometrics. [R package]
Ting Ye, Jun Shao, Hyunseung Kang (2021). Debiased Inverse-Variance Weighted Estimator in Two-Sample Summary-Data Mendelian Randomization. Annals of Statistics. [Slides, R package, Video]
Menghao Xu, Ting Ye, Jun-Jun Zhao, Menggang Yu (2021). Sample Size Determination for Stratified Phase II Cancer Trials with Monotone Order Constraints. Statistics in Biopharmaceutical Research.
Emily J. Mackay, Bo Zhang, Siyu Heng, Ting Ye, Mark D. Neuman, John G. Augoustides, Nimesh D. Desai, Peter W. Groeneveld (2021). Association Between Transesophageal Echocardiography (TEE) During Coronary Artery Bypass Graft (CABG) Surgery and Clinical Outcomes. Journal of the American Society of Echocardiography.
Shengqin Su, Gagan Chhabra, Mary Ann Ndiaye, Chandra K. Singh, Ting Ye, Wei Huang, Colin N. Dewey, Vijayasaradhi Setaluri, Nihal Ahmad (2021). PLK1 and NOTCH Positively Correlate in Melanoma and their Combined Inhibition Results in Synergistic Modulations of Key Melanoma Pathways. Molecular Cancer Therapeutics. [Featured cover article]
Ting Ye and Yanyao Yi (2021). Comment: Inference After Covariate-Adaptive Randomisation: Aspects of Methodology and Theory. Statistical Theory and Related Fields.
2020
Ting Ye and Jun Shao (2020). Robust Tests for Treatment Effect in Survival Analysis under Covariate-Adaptive Randomization. Journal of the Royal Statistical Society: Series B. [Paper, Slides]
Yanyao Yi, Ting Ye, Menggang Yu, Jun Shao (2020). Cox Regression with Survival‐Time‐Dependent Missing Covariate Values. Biometrics.
2019 and before
Chandra K. Singh, Charlotte A. Mintie, Mary A. Ndiaye, Gagan Chhabra, Panshak P. Dakup, Ting Ye, Menggang Yu, Nihal Ahmad (2019). Chemoprotective effects of dietary grape powder on ultraviolet B radiation-mediated skin carcinogenesis in SKH-1 hairless mice. Journal of Investigative Dermatology.
Ting Ye and Menggang Yu (2018). A Robust Approach to Sample Size Calculation in Cancer Immunotherapy Trials with Delayed Treatment Effect. Biometrics. [Slides]
Ting Ye (2018). Testing hypotheses under covariate-adaptive randomisation and additive models. Statistical Theory and Related Fields.
Muxuan Liang, Ting Ye, Haoda Fu (2018). Estimating Individualized Optimal Combination Therapies through Outcome Weighted Deep Learning Algorithms. Statistics in Medicine.
Ting Ye and Yanyao Yi (2017). Book Review "Sample Size Calculations in Clinical Research, third edition, by Shein-Chung Chow, Jun Shao, Hansheng Wang, and Yuliya Lokhnygina". Statistical Theory and Related Fields.
Xiaolin Zheng, Zhen Lin, Huan Xu, Chaochao Chen, Ting Ye (2015). Efficient Learning Ensemble SuperParent-one-dependence Estimator by Maximizing Conditional Log Likelihood. Expert Systems with Applications.
