28 Oct - 1 Nov 2013 (Stellenbosch) Introduction to the Joint Modeling of Longitudinal and Survival Data, with Applications in R. Course Completed

Posted on Mon, Mar 04 2013 16:40:00

Course Completed.

Dr. Dimitris Rizopoulos (Department of Biostatistics, Erasmus University Medical Center, the Netherlands) presented an intensive five-day course at Stellenbosch under the auspices of the South African DST/NRF Centre for Epidemiological Modeling and Analysis (SACEMA). The course took place from 9 am to 4 pm daily in the STIAS Library, adjacent to SACEMA.

For the full announcement, click here.

Course summary: In recent years there has been an increasing interest in the class of joint models for longitudinal and time-to-event data. These models constitute an attractive paradigm for the analysis of follow-up data that is mainly applicable in two settings: First, when focus is on a survival outcome and we wish to account for the effect of endogenous time-dependents covariates measured with error (e.g., biomarkers), and second, when focus is on the longitudinal outcome and we wish to correct for nonrandom dropout. This course is aimed for applied researchers and graduate students and will provide a comprehensive introduction into this modeling framework. In particular, we will explain when these models should be used in practice, which are the key assumptions behind them, and how they can be utilized to extract relevant information from the data. Emphasis will be given on applications and the use of the R packages JM and JMbayes. This course assumes knowledge of basic statistical concepts, such as standard statistical inference using maximum likelihood, and regression models. In addition, basic knowledge of R would be beneficial but is not required.


Dimitris Rizopoulos is an Assistant Professor in Biostatistics at the
Erasmus University Medical Center. He received a M.Sc. in statistics
(2003) from the Athens University of Economics and Business, and a Ph.D.
in biostatistics (2008) from the Katholieke Universiteit Leuven. Dr.
Rizopoulos wrote his dissertation, as well as a number of methodological
and applied articles on various aspects on models for survival and
longitudinal data analysis, and he is the author of a recent book on the
topic of joint models for longitudinal and time-to-event data. He has
also written two freely available packages to fit this type of models in
R under maximum likelihood (i.e., package JM) and the Bayesian approach
using JAGS, WinBUGS or OpenBUGS (i.e., package JMbayes). He currently
serves as an Associate Editor for Biometrics and Biostatistics, and he
has been a guest editor of a special issue on joint models in
Statistical Methods in Medical Research


Book websites:

For the full announcement, click here.