Vanke Chair Professor, Vanke School of Public Health, Tsinghua University

Research Interests

Statistical methodology: semiparametric methods, causal inference (comparative effectiveness analysis), dynamic treatment regimes/individualized treatment rule, survival data analysis/competing risk analysis, missing data, longitudinal data analysis, and clinical trials

Applications: Cardiovascular diseases and cardiac surgery, solid organ transplantation, kidney disease, respiratory diseases, aging, cancer etc.

Education

PhD, Statistics, North Carolina State University, 2008

MA, Ecology, Duke University, 2004

BS, Environmental Science (minor: Computer Science), Peking University, 2001

Positions

2023-present Professor (with tenure), Vanke School of Pubic Health, Tsinghua University, Beijing, China

2020-2023 Professor (with tenure), Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA

2015-2020 Associate Professor (with tenure), Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA

2008-2015 Assistant Professor, Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA

Editorial Services

Deputy Editor/Statistics Editor: Journal of Heart and Lung Transplantation

Associate Editor: Biometrics

Editorial Board: the International Journal of Biostatistics

Professional affiliations

American Statistical Association (ASA)

International Biometric Society (IBS), ENAR

International Chinese Statistical Association (ICSA)

The International Society for Heart and Lung Transplantation (ISHLT)

Selected Publications

Yang, G., Zhang, M., Zhou, S., Hou, H., Grady, K. L., Stewart II, J. W., Chenoweth, C. E., Aaronson, K. D., Fetters, M. D., Chandanabhumma, P. P., Aaronson, K. D., Pienta, M. J.,Malani, P. N., Hider, A. M., Cabrera, L., Pagani, F. D., and Likosky, D. S (2022). Incompleteness of health-related quality of life assessments before left ventricular assist device implant: A novel quality metric. The Journal of Heart and Lung Transplantation, 41(10), 1520-1528.

Yang, G., Zhang, B., Zhang, M. (2022). Estimation of Knots in Linear Spline Model. Journal of the American Statistical Association, Volume 118, 2023 - Issue 541，Pages 639-650.

Fang, Y., Zhang, B., Zhang, M. (2021). Robust Method for Optimal Treatment Decision Making Based on Survival Data. Statistics in Medicine, 40(29):6558-6576.

Dahmer, M.K., Yang, G., Zhang, M., Quasney, M.W., Sapru, A., Weeks, H.M., Sinha, P., Curley, M.A.Q., Delucchi, K.L., Calfee, C.S., Flori, H. (2021). Use of Latent Class Analysis in Identification of Phenotypes in Pediatric Acute Respiratory Distress Syndrome Patients, The Lancet Respiratory Medicine, 2022 Mar;10(3):289-297.

Donald S. Likosky, Guangyu Yang, Min Zhang, Preeti N. Malani, Michael D. Fetters, Raymond J. Strobel, Carol E. Chenoweth, Hechuan Hou, Francis D. Pagani. (2022). Interhospital Variability in Healthcare Associated Infections and Payments After Durable Ventricular Assist Device Implant among Medicare Beneficiaries. The Journal of Thoracic and Cardiovascular Surgery, 164(5):1561-1568.

Zhang, B. and Zhang, M. (2021). Subgroup identification and variable selection for treatment decision making. Annals of Applied Statistics, 16(1): 40-59 (March 2022). DOI: 10.1214/21-AOAS1468

Zhang, M., and Zhang, B. (2021). Discussion on "Improving precision and power in randomized trials for COVID-19 treatments using covariate adjustment, for binary, ordinal, and time-to-event outcomes" by David Benkeser, Ivan Diaz, Alex Luedtke, Jodi Segal, Daniel Scharfstein, and Michael Rosenblum. Biometrics, https://doi.org/10.1111/biom.13492.

Youfei Yu, Zhang M., Xu Shi Megan E. V. Caram Roderick J. A. Little Bhramar Mukherjee.(2021). A comparison of parametric propensity score-based methods for causal inference with multiple treatments and a binary outcome. Statistics in Medicine, 40(7):1653-1677.

Zhang, M. and Zhang, B. (2022). A stable and more efficient doubly robust estimator. Statistica Sinica， 32，1143-1163.

Song, Y., Zhou, X., Kang, J., Aung, M. T., Zhang, M., Zhao, W., Needham, B. L., Kardia, S.L.R., Liu, Y., Meeker, J.D., Smith, J.A., and Mukherjee (2021). Bayesian Hierarchical Models for High-Dimensional Mediation Analysis with Coordinated Selection of Correlated Mediators. Statistics in Medicine, https://doi.org/10.1002/sim.9168

Song, Y., Zhou, X., Kang, J., Aung, M. T., Zhang, M., Zhao, W., Needham, B. L., Kardia, S.L.R., Liu, Y., Meeker, J.D., Smith, J.A., and Mukherjee, B. (2021). Bayesian Sparse Mediation Analysis with Targeted Penalization of Natural Indirect Effects. Journal of the Royal Statistical Society C, 70(5): 1391–1412.

Sharma, P., Sui, Z., Zhang, M., Magee, J., Barman, P., Patel, Y., Schluger, A., Walter, K., Biggins, S., Cullaro, G., Wong, R., Lai, J., Jo, J., Sinha, J., VanWagner, L., Verna, E. (2021). Renal outcomes after Simultaneous Liver and Kidney Transplantation (SLKT): Results from the US Multicenter SLKT Consortium. Liver Transplantation, 27(8):1144-1153.

Bourque,J.L., Liang, Q., Pagani, F.D., Zhang, M., Thompson, M.P., Aaronson, K.D., Kormos, R.L., McCullough, J.S., Strobel, R.J., Palmer S., Watt, and T., Likosky, D.S. (2021). Durable Ventricular Assist Device Use in the United States by Geographic Region and Minority Status. The Journal of Thoracic and Cardiovascular Surgery, 161(1):123-33.

Su, F., Prashant Goteti, P., and Zhang, M. (2020). Unleashing the Power of Anomaly Data for Soft Failure Predictive Analytics. Proceedings of IEEE International Test Conference, 2020.

Zhang, M., Wang, S., He, Z., Salvatore, M., and Mukherjee., B. (2019). Interaction analysis under misspecification of main effects: Some common mistakes and simple solutions. Statistics in Medicine, 39(11): 1675-1694.

Song, Y., Zhou, X., Zhang, M., Wei Zhao, W., Yongmei Liu,Y., Kardia, S.L.R., Roux, A.V.D.,Needham, B.L., Smith, J.A., and Bhramar Mukherjee, B. (2019). Bayesian shrinkage estimation of high dimensional causal mediation effects in omics studies, Biometrics, 76(3):700-710.

Su, F., Goteti, P., Zhang, M. (2019). On freedom from interference in mixed-criticality systems: a causal learning approach. Proceedings of IEEE International Test Conference, 2019.

Zhang, Z., Liu, C., Ma, S., and Zhang, M. (2019). Estimating Mann-Whitney-type causal effects for right-censored survival outcomes. Journal of Causal Inference, 7(1).

Thompson, M., Pagani, F.D., Liang, Q., Franko, L.R., Zhang, M., McCullough, J.S., Strobel, R.J., Aaronson, K., Kormos, R.L., Likosky, D.S. (2019). Center variation in medicare spending for durable left ventricular assist device implant hospitalization. JAMA Cardiology, Jan 30. (doi:10.1001/jamacardio.2018.4717) (with invited commentary)

Zhang, B. and Zhang, M. (2018). Variable selection for estimating the optimal treatment regimes in the presence of a large number of covariates. Annals of Applied Statistics, 12(4), 2335-2358.

Zhang, B. and Zhang, M. (2018). C-learning: a new classification framework to estimate optimal dynamic treatment regimes. Biometrics, 74(3):891-899.

Liang, Q., Ward, S., Pagani, F.D., Sinha, S.S., Zhang, M., Kormos, R., Aaronson, K.D.,Althouse, A., Kirklin, J.K., Naftel, D., Likosky, D.S. (2018). Linkage of medicare files to the Interagency Registry of Mechanically Assisted Circulatory Support. The Annals of Thoracic Surgery 105(5):1397-1402.

Jung, M.S., Zhang, M., Askren, M.K., Berman, M.G., Peltier, S., Hayes, D.F., Therrien, B., Reuter-Lorenz, P.A., Cimprich, B. (2017). Cognitive dysfunction and symptom burden in womentreated for breast cancer: A prospective behavioral and fMRI analysis. Brain Imaging and Behavior,11(1):86-97. PMID: 26809289.

He, Z., Lee, S., Zhang, M., Smith, J.A., Guo, X., Palmas, W., Kardia, S.L.R., Ionita-Laza1, I., Mukherjee, B. (2017). Rare-variant association tests in longitudinal studies, with an application to the Multi-Ethnic Study of Atherosclerosis (MESA), Genetic Epidemiology, 41(8):801-810.

He, Z., Zhang, M., Lee, S., Smith, J.A., Kardia, S.L.R., Diez Roux, A.V., Mukherjee, B. (2017).Set-based tests for gene-environment interaction in longitudinal studies. Journal of the American Statistical Association, 112(519):966-978.

Strobel, R.J., Liang, Q, Zhang, M., Wu, X., Rogers, M.A.M., Theurer,P.F., Fishstrom, A.B., Harrington, S.D., DeLucia, A., Paone, G., Patel, H.J., Prager, R.L., Likosky, D.S. (2016). A pre-operative risk model for post-operative pneumonia following coronary artery bypass grafting. The Annals of Thoracic Surgery, 102(4):1213-9.

Likosky, D.S., Zhang, M., Paone, G., Collins, J., DeLucia, A., Schreiber, T., Theurer, P., Kazziha, S., Leffler, D., Wunderly, D.J., Gurm, H.S., Prager, R.L. (2016) Impact of Institutional Culture on Rates of Transfusions During Cardiovascular Procedures: The Michigan Experience. American Heart Journal, 174:1-6. (doi: 10.1016/j.ahj.2015.12.019. PMID: 26995363)

He, Z., Zhang, M., Lee, S., Smith, J.A., Guo, X., Palmas, W., Kardia, S.L.R., Roux, A.V.D., Mukherjee, B.(2015). Set-based tests for genetic association in longitudinal studies. Biometrics,71(3):606-15.

Zhang, M. (2015). Robust methods to improve efficiency and reduce bias due to chance imbalance in estimating survival curves in randomized clinical trials. Lifetime Data Analysis, 21(1),119-137.

He, Z., Zhang, M., Zhan, X., and Lu, Q. (2014). Modeling and testing for joint association using a genetic random field model. Biometrics, 70(3),471-479.

Shih, T., Zhang, M., Kommareddi, M., Boeve, T.J., Harrington,S.D., Holmes, R.J., Roth, G.,Theurer, P.F., Prager, R.L., Likosky, D.S. (2014). Center-level variation in infection rates after coronary artery bypass grafting. Circulation: Cardiovascular Quality and Outcomes, 7(4),567-573.

Nygaard, I., Brubaker, L., Zyczynski, H.M., Cundiff, G., Richter, H., Gantz, M., Fine, P., Menefee, S., Ridgeway, B., Visco, A., Warren, L.K., Zhang, M., Meikle, S. (2013). Long-term outcomes following abdominal sacrocolpopexy for pelvic organ prolapse. The Journal of the American Medical Association, 309(19), 2016-2024.

Zhang, M. and Wang, Y. (2013). Adjusting for observational secondary treatments in estimating the effects of randomized treatments. Biostatistics, 14(3),491-501.

Valle, J.A., Zhang, M., Dixon, S., Aronow, H.D., Share, D., Naoum, J.B., Gurm, H.S. (2013). Impact of pre-procedural beta blockade on inpatient mortality in patients undergoing primary PCI for ST elevation MI. The American Journal of Cardiology, 111(12), 1714-1720.

Zhang, B., Tsiatis, A.A., Davidian, M., Zhang, M., and Laber, E (2012). Estimating optimal treatment regimes from classification perspective. Stat, 1(1), 103-114.

Zhang, M. and Schaubel, D. E. (2012). Double-robust semiparametric estimator for differences in restricted mean lifetimes in observational studies. Biometrics, 68, 999-1009.

Zhang, M. and Schaubel, D. E. (2012). Contrasting treatment-specific survival using double robust estimators. Statistics in Medicine, 31(30), 4255-4268.

Zhang, M. and Wang, Y. (2012). Estimating treatment effects from a randomized trial in the presence of secondary treatment. Biostatistics, 13(4), 625-636.

Zhang, M. and Schaubel, D. E. (2011). Estimating differences in restricted mean lifetime using observational data subject to dependent censoring. Biometrics, 67, 740-749.

Piccini, J. P., Zhang, M., Pieper, K., Solomon, S. D., Al-Khatib, S. M., Van de Werf, F., Pfeffer M. A., McMurray, J.V. J., Califf, R. M., Velazquez, E. J. (2010). Predictors of sudden cardiac death change with time after myocardial infarction: results from the VALIANT Trial. European Heart Journal, 31(2), 211-21.

Zhang, M., Tsiatis, A. A., Davidian, M., Pieper, K. S., and Mahaffey, K. (2011). Inference on treatment effects from a randomized clinical trial in the presence of premature treatment discontinuation: The SYNERGY trial. Biostatistics, 12(2) 258-269.

Schaubel, D. E. and Zhang, M. (2010). Estimating treatment effects on the marginal recurrent event mean in the presence of a terminating event. Lifetime data analysis, 16(4), 451-477.

Zhang, M. and Gilbert, B. P. (2010). Increasing the efficiency of prevention trials by incorporating baseline covariates. Statistical Applications in Infectious Diseases. Vol. 2: Iss. 1, Article 1. (doi: 10.2202/1948-4690.1002).

Wang, T. Y., Zhang, M., Fu, Y., Armstrong, P. W., Newby, L. K., Gibson C. M., Moliterno, D.J., Van de Werf, F., White, H. D., Harrington, R. A., Roe, M. T. (2009). Incidence, distribution,and prognostic impact of occluded culprit arteries among patients with non-ST-elevation acutecoronary syndromes undergoing diagnostic angiography. American Heart Journal, 157(4), 716-723.

Zhang, M., Tsiatis, A.A., and Davidian, M. (2008). Improving efficiency of inferences in randomized clinical trials using auxiliary covariates. Biometrics, 64(3), 707-715.

Tsiatis, A.A., Davidian, M., Zhang, M., and Lu, X. (2008). Covariate adjustment for two-sample treatment comparisons in randomized clinical trials: A principled yet flexible approach. Statisticsin Medicine, 27(23), 4658-4677.

Zhang, M. and Davidian, M. (2008). "Smooth" semiparametric regression analysis for arbitrarily censored time-to-event data. Biometrics, 64(2), 567-576.

Contact Information

email: mzhangst@tsinghua.edu.cn