A photo of Nanhua Zhang.

Associate Professor, UC Department of Pediatrics


Biography & Affiliation


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 learning health systems, pediatric traumatic brain injury (TBI), environmental health, 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 Time.com and Yahoo.com.

Dr. Zhang has authored 85 peer-reviewed papers and made numerous presentations at national and international conferences. He has served as a reviewer for over 40 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.

Research Interests

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

Academic Affiliation

Associate Professor, UC Department of Pediatrics




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

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

PhD: University of Michigan, Ann Arbor, MI.


Zhang N, Kaizar EE, Narad M, Kurowski B, Yeates KO, Taylor HG, Wade, SL. Examination of Injury, Host, and Social-Environmental Moderators of Online Family Problem Solving Treatment Efficacy for Pediatric Traumatic Brain Injury Using an Individual Participant Data Meta-Analytic Approach. Journal of Neurotrauma. 2019;36(7):1147-55. 

Zhang Y, Chen H, Zhang N. Bayesian Inference for Nonresponse Two-phase Sampling. Statistica Sinica. 2018;28:2167-87.

Zhang N, Cheng S, Ambroggio L, Florin TA, Macaluso M. Accounting for misclassification bias of binary outcomes due to under-screening: a sensitivity analysis. BMC Medical Research Methodology. 2017;17(1):168. 

Zhang N, Chen H, Elliott MR. Nonrespondent Subsample Multiple Imputation in Two-phase Sampling for Nonresponse. Journal of Official Statistics. 2016;32(3):769-785.

Wade SL, Zhang N, Yeates KO, Stancin T, Taylor HG. Social Environmental Moderators of Long-term Functional Outcomes of Early Childhood Brain Injury. JAMA Pediatrics. 2016;170(4):343-9. 

Zhang N, Little RJA. Subsample ignorable likelihood for accelerated failure time models with missing predictors. Lifetime Data Anal. 2015;21(3):457-69.

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.

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.