Yimei Li, PhD



Yimei Li, PhD

Associate Professor of Biostatistics

Dr. Li’s methodology research interests include clinical trial design, survival analysis, longitudinal data analysis, and statistical methods for health services research. Her earlier research focused on survival analysis, specifically statistical methodology for multivariate time-to-event data with alternating states and a possibility of cure. Recently, she has focused her research on statistical designs and analyses for early phase cancer clinical trials, such as Bayesian adaptive designs for dose-finding trials and platform/basket trials. Her collaborative research focuses on pediatric oncology, including basic and translational research to understand tumor biology, clinical trials to evaluate experimental cancer therapies (such as CAR-T immunotherapy), epidemiological studies using real world data (RWD) such as administrative database and electronic health records (EHR), and behavioral and psycho-social studies that aim to help oncology patients/families cope and adjust to their medical experience.

Dr. Li has extensive experience in design, conduct and analysis of various cancer studies, and have published over 190 articles in the literatures of statistical methodology, cancer research, and other areas of medicine. She has been recognized for her statistical expertise by appointments to several national committees, such as being a standing member on the NIH Clinical Oncology study section and a member on NRG Oncology Data Monitoring Committee. She is also on the editorial board of the Journal of the National Cancer Institute, is a member of Statistical Advisory Panel for Nature Medicine, and serves as a grant reviewer for multiple funding agencies and as a manuscript reviewer for many prestigious statistical and cancer journals.


Content Area Specialties

Cancer, pediatrics, clinical trial, epidemiology, basic and translational research, psychosocial

Methodology Specialties

 Clinical trial design, survival analysis, longitudinal data analyses, statistical methods for health services research


About Us

To understand health and disease today, we need new thinking and novel science —the kind  we create when multiple disciplines work together from the ground up. That is why this department has put forward a bold vision in population-health science: a single academic home for biostatistics, epidemiology and informatics. 

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