Ting Ye
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Debiased inverse-variance weighted estimator in two-sample summary-data Mendelian randomization
T Ye, J Shao, H Kang
The Annals of statistics 49 (4), 2079-2100, 2021
Toward better practice of covariate adjustment in analyzing randomized clinical trials
T Ye, J Shao, Y Yi, Q Zhao
Journal of the American Statistical Association, 1-13, 2022
Association between transesophageal echocardiography and clinical outcomes after coronary artery bypass graft surgery
EJ MacKay, B Zhang, S Heng, T Ye, MD Neuman, JG Augoustides, ...
Journal of the American Society of Echocardiography 34 (6), 571-581, 2021
Inference on the average treatment effect under minimization and other covariate-adaptive randomization methods
T Ye, Y Yi, J Shao
Biometrika 109 (1), 33-47, 2022
Chemoprotective effects of dietary grape powder on UVB radiation-mediated skin carcinogenesis in SKH-1 hairless mice
CK Singh, CA Mintie, MA Ndiaye, G Chhabra, PP Dakup, T Ye, M Yu, ...
Journal of Investigative Dermatology 139 (3), 552-561, 2019
Robust tests for treatment effect in survival analysis under covariate-adaptive randomization
T Ye, J Shao
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020
A robust approach to sample size calculation in cancer immunotherapy trials with delayed treatment effect
T Ye, M Yu
Biometrics 74 (4), 1292-1300, 2018
Estimating individualized optimal combination therapies through outcome weighted deep learning algorithms
M Liang, T Ye, H Fu
Statistics in medicine 37 (27), 3869-3886, 2018
Sample size calculations in clinical research, by Shein-Chung Chow, Jun Shao, Hansheng Wang, and Yuliya Lokhnygina: Chapman & Hall/CRC Biostatistics Series, New York, Taylor …
T Ye, Y Yi
Statistical Theory and Related Fields 1 (2), 265-266, 2017
PLK1 and NOTCH positively correlate in melanoma and their combined inhibition results in synergistic modulations of key melanoma pathways
S Su, G Chhabra, MA Ndiaye, CK Singh, T Ye, W Huang, CN Dewey, ...
Molecular cancer therapeutics 20 (1), 161-172, 2021
GENIUS-MAWII: For robust Mendelian randomization with many weak invalid instruments
T Ye, Z Liu, B Sun, ET Tchetgen
arXiv preprint arXiv:2107.06238, 2021
Bridging preference‐based instrumental variable studies and cluster‐randomized encouragement experiments: Study design, noncompliance, and average cluster effect ratio
B Zhang, S Heng, EJ MacKay, T Ye
Biometrics 78 (4), 1639-1650, 2022
Instrumented difference‐in‐differences
T Ye, A Ertefaie, J Flory, S Hennessy, DS Small
Biometrics 79 (2), 569-581, 2023
Fifa: Making fairness more generalizable in classifiers trained on imbalanced data
Z Deng, J Zhang, L Zhang, T Ye, Y Coley, WJ Su, J Zou
arXiv preprint arXiv:2206.02792, 2022
On Mendelian randomization mixed-scale treatment effect robust identification (MR MiSTERI) and estimation for causal inference
Z Liu, T Ye, B Sun, M Schooling, ET Tchetgen
arXiv preprint arXiv:2009.14484, 2020
A negative correlation strategy for bracketing in difference-in-differences
T Ye, L Keele, R Hasegawa, DS Small
Journal of the American Statistical Association, 1-13, 2023
Cox regression with survival‐time‐dependent missing covariate values
Y Yi, T Ye, M Yu, J Shao
Biometrics 76 (2), 460-471, 2020
Testing hypotheses under covariate-adaptive randomisation and additive models
T Ye
Statistical Theory and Related Fields 2 (1), 96-101, 2018
Generalized Difference-in-Differences
DB Richardson, T Ye, EJT Tchetgen
Epidemiology, 10.1097, 2022
Minimax rates and adaptivity in combining experimental and observational data
S Chen, B Zhang, T Ye
arXiv preprint arXiv:2109.10522, 2021
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