Publications

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Zhao, Ying-Qi, and Michael R. Kosorok. "Discussion of combining biomarkers to optimize patient treatment recommendations." Biometrics 70, no. 3 (2014): 713-6.
Zhao, Jingkang, Dongshunyi Li, Jungkyun Seo, Andrew S. Allen, and Raluca Gordân. "Quantifying the Impact of Non-coding Variants on Transcription Factor-DNA Binding." Res Comput Mol Biol 10229 (2017): 336-352.
Zhao, Yue, Amy H. Herring, Haibo Zhou, Mirza W. Ali, and Gary G. Koch. "A multiple imputation method for sensitivity analyses of time-to-event data with possibly informative censoring." J Biopharm Stat 24, no. 2 (2014): 229-53.
Zhao, Yingqi. Estimation of Optimal Dynamic Treatment Regimes., 2014.
Zhao, Yufan, Donglin Zeng, Mark A. Socinski, and Michael R. Kosorok. "Reinforcement learning strategies for clinical trials in nonsmall cell lung cancer." Biometrics 67, no. 4 (2011): 1422-33.
Zhao, Ying-Qi, Donglin Zeng, Eric B. Laber, and Michael R. Kosorok. "New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes." J Am Stat Assoc 110, no. 510 (2015): 583-598.
Zhao, Guolin, Rachel Marceau, Daowen Zhang, and Jung-Ying Tzeng. "Assessing gene-environment interactions for common and rare variants with binary traits using gene-trait similarity regression." Genetics 199, no. 3 (2015): 695-710.
Zhao, Yingqi, Donglin Zeng, John A Rush, and Michael R. Kosorok. "Estimating Individualized Treatment Rules Using Outcome Weighted Learning." J Am Stat Assoc 107, no. 449 (2012): 1106-1118.
Zhao, Luping. Measures of Clinical Benefit in Immuno-Oncology Studies., 2016.
Zhao, Ying-Qi, Eric B. Laber, Yang Ning, Sumona Saha, and Bruce E. Sands. "Efficient augmentation and relaxation learning for individualized treatment rules using observational data." J Mach Learn Res 20 (2019).
Zhou, Haibo, Yuanshan Wu, Yanyan Liu, and Jianwen Cai. "Semiparametric inference for a 2-stage outcome-auxiliary-dependent sampling design with continuous outcome." Biostatistics 12, no. 3 (2011): 521-34.
Zhou, Jie, Jiajia Zhang, and Wenbin Lu. ICGOR: Fit Generalized Odds Rate Hazards Model with Interval Censored Data (R). 2.0 ed., 2017.
Zhou, Jie, Jiajia Zhang, and Wenbin Lu. GORCure: Fit Generalized Odds Rate Mixture Cure Model with Interval Censored Data (R)., 2017.
Zhou, Q, H Zhou, and J Cai. "Case-cohort studies with interval-censored failure time data." Biometrika 104, no. 1 (2017): 17-29.
Zhou, Yi-Hui. mcc: Moment corrected correlation an approximation to exact association testing of two vectors (R).. 1.0 ed., 2014.
Zhou, Qingning, Jianwen Cai, and Haibo Zhou. "Outcome-dependent sampling with interval-censored failure time data." Biometrics 74, no. 1 (2018): 58-67.
Zhou, Fan, Haibo Zhou, Tengfei Li, and Hongtu Zhu. "Analysis of secondary phenotypes in multigroup association studies." Biometrics 76, no. 2 (2020): 606-618.
Zhou, Yi-Hui, William T. Barry, and Fred A. Wright. "Empirical pathway analysis, without permutation." Biostatistics 14, no. 3 (2013): 573-85.
Zhou, Yi-Hui, and Fred A. Wright. "Hypothesis testing at the extremes: fast and robust association for high-throughput data." Biostatistics 16, no. 3 (2015): 611-25.
Zhou, Jie, Jiajia Zhang, Alexander C. Mclain, Wenbin Lu, Xuemei Sui, and James W. Hardin. "A varying-coefficient generalized odds rate model with time-varying exposure: An application to fitness and cardiovascular disease mortality." Biometrics 75, no. 3 (2019): 853-863.
Zhou, Haibo, Wangli Xu, Donglin Zeng, and Jianwen Cai. "Semiparametric Inference for Data with a Continuous Outcome from a Two-Phase Probability Dependent Sampling Scheme." J R Stat Soc Series B Stat Methodol 76, no. 1 (2014): 197-215.
Zhou, Hua, Lexin Li, and Hongtu Zhu. "Tensor Regression with Applications in Neuroimaging Data Analysis." J Am Stat Assoc 108, no. 502 (2013): 540-552.
Zhou, Qingning, Jianwen Cai, and Haibo Zhou. "Semiparametric inference for a two-stage outcome-dependent sampling design with interval-censored failure time data." Lifetime Data Anal 26, no. 1 (2020): 85-108.
Zhou, Jie, Jiajia Zhang, and Wenbin Lu. "An Expectation Maximization algorithm for fitting the generalized odds-rate model to interval censored data." Stat Med 36, no. 7 (2017): 1157-1171.
Zhou, Xin, Nicole Mayer-Hamblett, Umer Khan, and Michael R. Kosorok. "Residual Weighted Learning for Estimating Individualized Treatment Rules." J Am Stat Assoc 112, no. 517 (2017): 169-187.
Zhou, Jie, Jiajia Zhang, and Wenbin Lu. "Computationally Efficient Estimation for the Generalized Odds Rate Mixture Cure Model with Interval-Censored Data." J Comput Graph Stat 27, no. 1 (2018): 48-58.
Zhu, Hongtu, Martin Styner, Yimei Li, Linglong Kong, Yundi Shi, Weili Lin, Christopher Coe, and John H. Gilmore. "Multivariate varying coefficient models for DTI tract statistics." Med Image Comput Comput Assist Interv 13, no. Pt 1 (2010): 690-7.
Zhu, Wensheng, Donglin Zeng, and Rui Song. "Proper Inference for Value Function in High-Dimensional Q-Learning for Dynamic Treatment Regimes." J Am Stat Assoc 114, no. 527 (2019): 1404-1417.
Zhu, Hongtu, Joseph G. Ibrahim, and Hyunsoon Cho. "PERTURBATION AND SCALED COOK'S DISTANCE." Ann Stat 40, no. 2 (2012): 785-811.
Zhu, Hongtu, Joseph G. Ibrahim, and Niansheng Tang. "Bayesian influence analysis: a geometric approach." Biometrika 98, no. 2 (2011): 307-323.
Zhu, Zhaoyin, Xiaofei Wang, Paramita Saha-Chaudhuri, Andrzej S. Kosinski, and Stephen L. George. "Time-dependent classification accuracy curve under marker-dependent sampling." Biom J 58, no. 4 (2016): 974-92.
Zhu, Hongtu, Joseph G. Ibrahim, and Hyunsoon Cho. Perturbation and scaled Cook's distance (C++/Matlab).., 2012.
Zhu, Ruoqing, Ying-Qi Zhao, Guanhua Chen, Shuangge Ma, and Hongyu Zhao. "Greedy outcome weighted tree learning of optimal personalized treatment rules." Biometrics 73, no. 2 (2017): 391-400.
Zhu, Anqi, Joseph G. Ibrahim, and Michael I. Love. apeglm: Approximate posterior estimation for GLM coefficients (R)., 2018.
Zhu, Hongtu, Joseph G. Ibrahim, Hyunsoon Cho, and Niansheng Tang. "Bayesian Case Influence Measures for Statistical Models with Missing Data." J Comput Graph Stat 21, no. 1 (2012): 253-271.
Zhu, Hongtu, Joseph G. Ibrahim, and Qingxia Chen. "Bayesian Case-deletion Model Complexity and Information Criterion." Stat Interface 7, no. 4 (2014): 531-542.
Zhu, Hongtu, Joseph G. Ibrahim, Yueh-Yun Chi, and Niansheng Tang. "Bayesian influence measures for joint models for longitudinal and survival data." Biometrics 68, no. 3 (2012): 954-64.
Zhu, Hongtu, Runze Li, and Linglong Kong. "MULTIVARIATE VARYING COEFFICIENT MODEL FOR FUNCTIONAL RESPONSES." Ann Stat 40, no. 5 (2012): 2634-2666.
Zhu, Hongtu, Joseph G. Ibrahim, and Niansheng Tang. "Bayesian Sensitivity Analysis of Statistical Models with Missing Data." Stat Sin 24, no. 2 (2014): 871-896.
Zhu, Ruoqing, Donglin Zeng, and Michael R. Kosorok. "Reinforcement Learning Trees." J Am Stat Assoc 110, no. 512 (2015): 1770-1784.
Zhu, Hongtu, Linglong Kong, Runze Li, Martin Styner, Guido Gerig, Weili Lin, and John H. Gilmore. "FADTTS: functional analysis of diffusion tensor tract statistics." Neuroimage 56, no. 3 (2011): 1412-25.
Zhu, Ruoqing, and Michael R. Kosorok. "Recursively Imputed Survival Trees." J Am Stat Assoc 107, no. 497 (2012): 331-340.
Zhu, Hongtu, Joseph G. Ibrahim, and Ming-Hui Chen. "Diagnostic Measures for the Cox Regression Model with Missing Covariates." Biometrika 102, no. 4 (2015): 907-923.
Zhu, Ruoqing, Donglin Zeng, and Michael R. Kosorok. Reinforcement learning trees In The University of North Carolina at Chapel Hill Department of Biostatistics Technical Report Series. UNC at Chapel Hill. Chapel Hill: The University of North Carolina, 2012.
Zhu, Ruoqing, and Michael R. Kosorok. RLT: Reinforcement learning trees (R).. 2.0 ed., 2015.
Zhu, Anqi, Joseph G. Ibrahim, and Michael I. Love. "Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences." Bioinformatics 35, no. 12 (2019): 2084-2092.
Zhu, Hongtu, Zakaria Khondker, Zhaohua Lu, and Joseph G. Ibrahim. "Bayesian Generalized Low Rank Regression Models for Neuroimaging Phenotypes and Genetic Markers." J Am Stat Assoc 109, no. 507 (2014): 997-990.
Zou, Baiming, Fei Zou, Jonathan J. Shuster, Patrick J. Tighe, Gary G. Koch, and Haibo Zhou. "On variance estimate for covariate adjustment by propensity score analysis." Stat Med 35, no. 20 (2016): 3537-48.
Zou, Baiming, Jianwen Cai, Gary G. Koch, Haibo Zhou, and Fei Zou. "A model-based conditional power assessment for decision making in randomized controlled trial studies." Stat Med 36, no. 30 (2017): 4765-4776.
Zou, Baiming, Bo Jin, Gary G. Koch, Haibo Zhou, Stephen E. Borst, Sandeep Menon, and Jonathan J. Shuster. "On model selections for repeated measurement data in clinical studies." Stat Med 34, no. 10 (2015): 1621-33.

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