Min Zhang, Ph.D., is an Assistant Professor in the Department of Biostatistics at the University of Michigan. She received her Ph.D. in Statistics from North Carolina State University in 2008 and joined the faculty at the University of Michigan in the same year. Her research has been focused on semiparametric methods, causal inference, longitudinal data analysis, survival data analysis, missing data and clinical trials. She has been collaborating with investigators at Duke Clinical Research Institute (DCRI) on cardiovascular disease research and she served as a senior statistician in Data Coordinating Center (DCC) of the Pelvic Floor Disorders Network (PFDN). Since 2009, Dr. Zhang collaborates heavily with investigators at University of Michigan Kidney Epidemiology and Cost Center (KECC) and has been working on Scientific Registry of Transplant Recipients (SRTR) data sets and on projects involving evaluation of dialysis facilities. She is also a co-investigator on a study on cognitive function in patients with breast cancer.
BIOSTAT675: Survival Time Analysis
BIOSTAT685: Elements of Nonparametric Statistics
BIOSTAT870: Analysis of Repeated Measurements
Ph.D, Statistics, North Carolina State University, 2008
M.A., Ecology, Duke University, 2004
B.S., Environmental Science (minor: Computer Science), Peking University, 2001
Research Interests & Projects
My research interests include semiparametric methods with missing and censored data, clinical trials, causal inference, survival analysis, and longitudinal data analysis. I have also been collaborating with clinicians and medical doctors in cardiovascular diseases at Duke Clinical Research Institute.
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Zhang, M. and Wang, Y. (2012). Adjusting for observational secondary treatments in estimating the effects of randomized treatments. Biostatistics, In press
Zhang, M. and Schaubel, D. E. (2012). Contrasting treatment-specific survival using double-robust estimators. Statistics in Medicine, In Press
Zhang, M. and Wang, Y (2012). Estimating treatment effects from a randomized trial in the presence of a secondary treatment. Biostatistics, in press.
Zhang, M. and Schaubel, D. E. (2012). Double-robust semiparametric estimator for differences in restricted mean lifetimes in observational studies. Biometrics, In Press.
Zhang, M. and Schaubel, D. E. (2011). Estimating differences in restricted mean lifetime using observational data subject to dependent censoring. Biometrics, 67, 740-749.
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, 258-269.
Zhang, M. and Gilbert, B. P. (2010). Increasing the efficiency of prevention trials by incorporating baseline covariates. Statistical Applications in Infectious Diseases, 2(1)
Wang, T. Y., Zhang, M., Fu, Y., Armstrong, P. W., Newby, K. L., Gibson M. C., 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 Acute Coronary Syndromes Undergoing Diagnostic Angiography. American Heart Journal, 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, 707-715.
Zhang, M. and Davidian, M. (2008). "Smooth" semiparametric regression analysis for arbitrarily censored time-to-event data. Biometrics, 64, 567-576.
American Statistical Association
International Biometric Society, ENAR
International Society of Clinical Biostatistics (ISCB)