Jing Cheng, MD, MS, PhD
Dr. Cheng is a Professor in the UCSF Division of Oral Epidemiology & Dental Public Health and Division of Biostatistics. She is also the Director of Statistics and Informatics Core at Center for Tobacco Control Research and Education, a faculty member in the UCSF Center to Address Disparities in Children’s Oral Health (CAN DO), the Helen Diller Family Comprehensive Cancer Center, and the Clinical & Translational Science Institute (CTSI). Dr. Cheng is a well-known biostatistician, an elected fellow of the American Statistical Association (ASA), and 2020 Chair of the ASA Section on Statistics in Epidemiology. Dr. Cheng is Associate Editor and on editorial board of several scientific journals, and has been invited to provide scientific review for 30 scientific journals, NIH/NIDCR special review panels, and NIH/CSR Clinical Oncology Study Section.
Dr. Cheng earned her medical degree in China, M.S. in nutrition at Cornell University in 2002, and Ph.D. in biostatistics at the University of Pennsylvania in 2006. Before joining UCSF School of Dentistry in 2010, Dr. Cheng was an Assistant Professor in Biostatistics at the University of Florida’s College of Medicine.
Dr. Cheng develops new statistical methods for complex problems in randomized trials and observational studies. Dr. Cheng is principal investigator (PI) of various projects, developing statistical methods to better understand the effects of a treatment or program on health outcomes in studies with challenging problems and the underlying mechanisms of the treatment via biomarkers, behaviors and social factors. Dr. Cheng's researches provide investigators evidence to understand the causal pathway/mechanism of the treatment and improve future programs by tailoring specific components of the treatment in specific populations.
Dr. Cheng also works with investigators in various fields of health sciences, including dentistry and oral diseases, biomedicine, cancer, infectious diseases, pharmacogenomics, nursing, and public policy research, on study design, power analysis, randomization, statistical analysis, and the preparation of grant proposals and manuscripts.
Interests: causal inference (instrumental variables and propensity scores) with applications in clinical trials with complex issues, e.g., noncompliance, mediation through intermediate variables (biomarkers, attitude, knowledge, behaviors etc.), missing data, and outcomes only observed in “survivors” etc., and in observational studies with measured and unmeasured confounding, methods for genetic association studies, categorical data analysis, longitudinal data analysis, survey design and analysis, and nonparametric statistics