Nanhua Zhang, PhD

Academic Affiliations

Assistant Professor, UC Department of Pediatrics

Phone 513-803-9108


Missing data; comparative effectiveness; clinical trial design; meta-analysis; scale development; joint modeling; environmental health; community-based intervention; health disparity; behavioral intervention; health psychology

Dr. Zhang earned his PhD in biostatistics from the University of Michigan in Ann Arbor. Prior to joining Cincinnati Children’s Hospital Medical Center, he was a faculty member at the University of South Florida in Tampa. His statistical methodology research has covered missing data, causal inference, clinical trial design, joint modeling and meta-analysis. His applied research interests include environmental health, community-based intervention, health disparity, behavioral intervention and health psychology. His research “early childhood lead exposure on academic achievement” received media coverage on TV, radio, newspapers, magazines, and various online media such as and

Dr. Zhang has authored 20 published papers and made numerous presentations at national and international conferences. He has served as a reviewer for 15 different journals including: Biometrika, Statistics in Medicine, Statistics Sinica, Annals of Applied Statistics, American Journal of Public Health, Annals of Epidemiology, Health Education Research. He has taught graduate and advanced doctoral courses in linear models, survival analysis and statistical computing.

BS: Shanghai University of Finance and Economics, Shanghai, China.

MS: Bowling Green State University, Bowling Green, OH.

PhD: University of Michigan, Ann Arbor, MI.

View PubMed Publications

Zhang N, Little RJA. Subsample ignorable likelihood for accelerated failure time models with missing predictors. Lifetime Data Anal. 2014 Aug 5.

Huang Y, Xing D, Zhang N, Chen H. Jointly Modeling Event Time and Skewed-Longitudinal Data with Missing Response and Mismeasured Covariate. J Biopharm Stat. 2014 Jun 6.

Zhang N, Chen H, Zou Y. A joint model of binary and longitudinal data with non-ignorable missingness, with application to marital stress and late life depression. J Applied Statistics. 2014;41(5);1028-39.

Brannick MT, Zhang N. Bayesian Meta-analysis of Coefficient Alpha. Res Synthesis Methods. 2013;4(2):198-207.

Chen H, Zhang N, Lu X, Chen S. Caution regarding the choice of standard deviations to guide sample size calculations in clinical trials. Clin Trials. 2013 Aug;10(4)522-9.

Zhang N, Baker HW, Tufts M, Raymond RE, Salihu H, Elliott MR. Early childhood lead exposure and academic achievement: evidence from Detroit Public Schools (2008-2010). Am J Public Health. 2013 Mar;103(3):e72-7.

Zhang N, Little RJA. A pseudo-Bayesian approach to regression with missing covariates. Biometrics. 2012 Sep;68(3):933-42.

Little RJA, Zhang N. Subsample ignorable likelihood for regression with missing data. J R Stat Soc Ser C Appl Stat. 2011;60, 591-605.

Resnicow K, Zhang N, Vaughan R, Reddy SP, James S, Murry DM. When intraclass correlation coefficients go awry: a case study from a school-based smoking prevention study in South Africa. Am J Public Health. 2010 Sep;100(9):1714-48.

Resnicow K, Davis RE, Zhang N, Strecher VJ, Tolsma D, Calvi J, Alexander G, Anderson JP, Wiese C. Tailoring a fruit and vegetable intervention on ethnic identity: results of a randomized study. Health Psychol. 2009 Jul;28(4):394–403.