Survival Analysis

In many medical and scientific studies, investigators are interested in analyzing data on time to an event. Applications of this work arise in areas as diverse as medicine, epidemiology, demography, and engineering. In such event history data, interest centers on the timing and occurrence of various kinds of events such as repeated infections, recurrences of disease, or sequences of events that occur through the study period. Further generalizations of these problems include issues of competing risks, complex sampling and censoring mechanisms, and incorporation of time-dependent or longitudinal covariates. The analysis of survival data is an area of great strength in this department. Several of our faculty and students are working in this general area and have made important and fundamental contributions through many research articles, books, and applications. A variety of approaches for the analysis of survival data, including frequentist and Bayesian methods, are being developed at Michigan.

Faculty: M. Banerjee, K. He, N. Henderson, J. Kalbfleisch, Y. Li, A. Sen, M. Schipper, J. Taylor, A. Tsodikov, W. Ye, L. Zhao, M. Zhang

Links: UM General Clinical Research Center, UM Rogel Cancer Center, Kidney Epidemiology & Cost Center