The Statistics in Epidemiology Section will sponsor a JSM short course on the joint modeling of longitudinal and survival data, taught by Joseph G. Ibrahim, on August 10 from 8:30 a.m. – 5:00 p.m. For registration and pricing, please check the JSM 2015 website.
This short course will examine in-depth statistical methods for joint modeling of longitudinal and survival data. Both frequentist and Bayesian approaches will be discussed. The types of joint models we’ll cover include trajectory models and shared parameter models. Both linear mixed models and generalized linear mixed models will be discussed for the longitudinal models, while Cox-type and cure rate models will be discussed for the survival component. Both univariate and multivariate survival models will be discussed, as well as multivariate longitudinal models.
Several types of applications will be covered, including ones in cancer and AIDS research. Missing data issues will be examined, and SAS software for fitting joint models will be illustrated.
Ibrahim is the Alumni Distinguished Professor of Biostatistics at the The University of North Carolina Gillings School of Global Public Health. He has published more than 260 research papers, most of which are in top statistical journals. He has written two books at the advanced graduate level on Bayesian survival analysis and Monte Carlo methods in Bayesian computation. He is a fellow of the ASA and Institute of Mathematical Statistics and an elected member of the International Statistical Institute.
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