Faculty Profile

Yun  Li, PhD

Yun Li, PhD

  • Research Associate Professor
  • M4073 SPH II
  • 1415 Washington Heights
  • Ann Arbor, Michigan 48109-2029

Yun Li is a Research Associate Professor of Biostatistics. She received her PhD in Biostatistics from the University of Michigan in 2008 and joined the faculty that same year. Prior to her doctoral studies, she worked as a biostatistician at Duke Clinical Research Institute for two years, after she completed her Masters in Biostatistics from the University of North Carolina at Chapel Hill. She is currently a member of the University of Michigan Comprehensive Cancer Center, the Arbor Research Collaborative for Health and the Kidney Epidemiology and Cost Center. She has a wide range of methodological interests and has applied biostatistics to a number of scientific areas.

  • PhD, Biostatistics, University of Michigan, 2008
  • M.S., Biostatistics, University of North Carolina at Chapel Hill, 2001

I am interested in causal inference, missing data issues, Bayesian inference, surrogate and auxiliary data issues, mediation, intermediate outcomes, cancer statistics, mixed models, survival analysis and observational studies. I am currently developing statistical methods to quantify the causal relationship between an intermediate variable and a true endpoint in the presence of a treatment. I am also examining the impact of unmeasured confounders in observational studies. I am particularly interested in developing statistical methods motivated by real world problems in medical research.

I collaborate primarily in health sciences, particularly in the areas of cancer, liver and kidney disease and cardiovascular disease. In cancer research, I had examined how tissue and serum markers are related to tumor recurrence and survival. I am currently investigating the factors that impact the variation of treatment receipts and the degree of individualized care with the Cancer Surveillance & Outcomes Research Team (CanSORT). The team website is http://www.med.umich.edu/cansort/.  I have also been extensively collaborating with Arbor Research on the Dialysis Outcomes and Practice Patterns Study (DOPPS) to investigate how the differences in practice patterns correlate with outcome differences among patients with kidney disease. The study website is http://www.dopps.org/. In the area of liver disease, I have studied the mechanisms and causes of liver disease such as biliary atresia and neonatal hepatitis among young children. These collaborations have great potential in helping understand the factors associated with patient outcomes, improving care and lowering mortality and morbidity. Being a biostatistician, I believe in the importance of having good understanding of the science behind the data and the active involvement in every stage of the medical research.