Session Chair Profile
Ph.D., Professor of Biostatistics, Johns Hopkins University
Scott L. Zeger is co-Director of Hopkins inHealth, the Johns Hopkins precision medicine partnership of the University, Health System, and Applied Physics Laboratory. He conducts statistical research on Bayesian hierarchical models for better estimating an individual’s state, trajectory, or likely treatment benefits from clinical cohort data. Professor Zeger is a member of the Springer-Verlag editorial board for statistics and was the founding co-editor of the Oxford University Press journal Biostatistics. His work has been recognized with several awards including most recently an honorary doctorate from England’s Lancaster University and the 2015 Karl Pearson Prize from the International Statistical Institute with long-time colleague Dr. Kung-Yee Liang. Dr. Zeger is a Golden Apple Awardee for excellence in teaching.
Session Synopsis: Health practitioners ground clinical decisions for an individual patient on data garnered from patients with similar characteristics, or so called subgroups or subsets. The idea is to reference each individual patient against a population of otherwise similar patients to answer clinical questions about that patient’s health state, disease trajectory, and likely response to treatment. The goal of “subsetting” is to create increasingly homogenous groups of “otherwise similar patients” against whom to reference the individual patient. This session will discuss the learnings from analyzing subgroups and tying it to the biology of the system.