Ying‐Qi Zhao

发表

Using pilot data to size a two‐arm randomized trial to find a nearly optimal personalized treatment strategy

Rui Song, Donglin Zeng, Marie Davidian, 2016, Statistics in medicine.

On sparse representation for optimal individualized treatment selection with penalized outcome weighted learning

Donglin Zeng, Eric B. Laber, Eric Laber, 2015, Stat.

Estimation of optimal dynamic treatment regimes

Eric B. Laber, Ying‐Qi Zhao, 2014, Clinical trials.

Recent development on statistical methods for personalized medicine discovery

D. Zeng, Ying‐Qi Zhao, 2013, Frontiers of Medicine.

Robust Hybrid Learning for Estimating Personalized Dynamic Treatment Regimens

Michael R. Kosorok, Donglin Zeng, Ying Liu, 2016, 1611.02314.

Sample Size Calculations for SMARTs

Eric B. Laber, M. Kosorok, M. Davidian, 2019, 1906.06646.

Estimation and inference on high-dimensional individualized treatment rule in observational data using split-and-pooled de-correlated score

Muxuan Liang, Young-Geun Choi, Yang Ning, 2020, J. Mach. Learn. Res..

Penalty-based spatial smoothing and outlier detection for childhood obesity surveillance from electronic health records

Ying‐Qi Zhao, L. Hanrahan, D. Norton, 2018, 1804.05430.

Handling Nonmonotone Missing Data with Available Complete-Case Missing Value Assumption

Yen-Chi Chen, Ying‐Qi Zhao, G. Cheng, 2022, 2207.02289.

Efficient augmentation and relaxation learning for individualized treatment rules using observational data

Yang Ning, Eric B. Laber, Ying-Qi Zhao, 2019, J. Mach. Learn. Res..

Sizing a phase II trial to find a nearly optimal personalized treatment strategy

Eric B. Laber, M. Kosorok, M. Davidian, 2014 .

Efficient surrogate-assisted inference for patient-reported outcome measures with complex missing mechanism

Ying‐Qi Zhao, Jaeyoung Park, Muxuan Liang, 2022, 2210.09362.

Inference about the expected performance of a data-driven dynamic treatment regime

Eric B. Laber, Bibhas Chakraborty, Eric B Laber, 2014, Clinical trials.

New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes

Donglin Zeng, Michael R Kosorok, Eric B. Laber, 2015, Journal of the American Statistical Association.

Inference for Optimal Dynamic Treatment Regimes Using an Adaptive m‐Out‐of‐n Bootstrap Scheme

Yingqi Zhao, Eric B. Laber, Bibhas Chakraborty, 2013, Biometrics.

Estimating Individualized Treatment Rules Using Outcome Weighted Learning

Donglin Zeng, Yingqi Zhao, A John Rush, 2012, Journal of the American Statistical Association.

Designing precision medicine trials to yield a greater population impact

M. LeBlanc, Ying‐Qi Zhao, 2019, Biometrics.

Semiparametric and nonparametric methods in data mining and statistical learning with applications in public health surveillance and personalized medicine

Yingqi Zhao, Ying‐Qi Zhao, 2012 .

Inverse Regression Estimation for Censored Data

M. Kosorok, Ying‐Qi Zhao, N. V. Nadkarni, 2011, Journal of the American Statistical Association.

Efficient surrogate-assisted inference for patient-reported outcome measures with complex missing mechanism

Ying‐Qi Zhao, Jaeyoung Park, Muxuan Liang, 2022, 2210.09362.

Multicategory Outcome Weighted Margin-based Learning for Estimating Individualized Treatment Rules.

Yufeng Liu, Haoda Fu, Chong Zhang, 2020, Statistica Sinica.

Electronic health records and community health surveillance of childhood obesity.

Aman Tandias, Ying-Qi Zhao, Lawrence P Hanrahan, 2015, American journal of preventive medicine.

Augmented outcome‐weighted learning for estimating optimal dynamic treatment regimens

Ying Liu, Donglin Zeng, Yingqi Zhao, 2018, Statistics in medicine.

Regularized outcome weighted subgroup identification for differential treatment effects

Menggang Yu, Ying-Qi Zhao, Sijian Wang, 2015, Biometrics.

Dynamic Treatment Regimes: Statistical Methods for Precision Medicine

Ying‐Qi Zhao, 2022, Journal of the American Statistical Association.

Improved Doubly Robust Estimation in Learning Optimal Individualized Treatment Rules

Ying-Qi Zhao, Yinghao Pan, Ying‐Qi Zhao, 2020, Journal of the American Statistical Association.

Restricted survival benefit with right‐censored data

M. LeBlanc, Ying‐Qi Zhao, Shixiao Zhang, 2021, Biometrical journal. Biometrische Zeitschrift.

Quantifying treatment effects using the personalized chance of longer survival

Ying-Qi Zhao, Mary W Redman, Michael L LeBlanc, 2019, Statistics in medicine.

Discussion of combining biomarkers to optimize patient treatment recommendations

Michael R Kosorok, Ying-Qi Zhao, M. Kosorok, 2014, Biometrics.

Small area estimation and childhood obesity surveillance using electronic health records

Ying‐Qi Zhao, L. Hanrahan, D. Norton, 2021, PloS one.

Penalty-based spatial smoothing and outlier detection for childhood obesity surveillance from electronic health records

Young-Geun Choi, Lawrence P. Hanrahan, Derek L. Norton, 2018, 1804.05430.

Active Clinical Trials for Personalized Medicine

Guang Cheng, Stanislav Minsker, Ying-Qi Zhao, 2014, Journal of the American Statistical Association.

Robustifying Trial-Derived Optimal Treatment Rules for A Target Population.

Donglin Zeng, Ying-Qi Zhao, M. LeBlanc, 2019, Electronic journal of statistics.

Simultaneous spatial smoothing and outlier detection using penalized regression, with application to childhood obesity surveillance from electronic health records

Young-Geun Choi, Ying-Qi Zhao, Lawrence P Hanrahan, 2020, Biometrics.

Constructing time-invariant dynamic surveillance rules for optimal monitoring schedules.

Yingye Zheng, Ying‐Qi Zhao, L. Newcomb, 2023, Biometrics.

What Matters When It Comes to Trust in One's Physician: Race/Ethnicity, Sociodemographic Factors, and/or Access to and Experiences with Health Care?

Ying‐Qi Zhao, P. Rathouz, R. Schwei, 2020, Health equity.

Sample size estimation in educational intervention trials with subgroup heterogeneity in only one arm

Jianwen Cai, Ying‐Qi Zhao, D. Esserman, 2013, Statistics in medicine.

Long-term effect estimation when combining clinical trial and observational follow-up datasets

Yen-Chi Chen, J. Unger, Ying‐Qi Zhao, 2022, 2204.04309.

Inference for Optimal Dynamic Treatment Regimes Using an Adaptive m‐Out‐of‐n Bootstrap Scheme

Eric B. Laber, B. Chakraborty, Ying‐Qi Zhao, 2013, Biometrics.

Estimation and inference on high-dimensional individualized treatment rule in observational data using split-and-pooled de-correlated score

Maureen A. Smith, Y. Ning, Ying‐Qi Zhao, 2020, J. Mach. Learn. Res..

Greedy outcome weighted tree learning of optimal personalized treatment rules

Shuangge Ma, Hongyu Zhao, Ruoqing Zhu, 2017, Biometrics.

Detecting Disease Outbreaks Using Local Spatiotemporal Methods

Amy Ising, Donglin Zeng, Yingqi Zhao, 2011, Biometrics.