Bayesian Analysis of Longitudinal Studies, 26-27 November 2015, Stellenbosch,
South Africa (early bird registration deadline: 30 September 2015)
Prof. Emmanuel Lesaffre of the Leuven Biostatistics and Statistical
Bioinformatics Centre (L-BioStat), Catholic University of Leuven, Belgium, will
be presenting this intensive two-day course at Stellenbosch under the auspices
of the South African DST/NRF Centre for Epidemiological Modelling and Analysis
(SACEMA). The course will take place from 9 am to 4 pm daily at the
Stellenbosch Institute for Advanced Study (STIAS).
The total course fee, including refreshments, lunches and social events, is
R3000 for early bird registration by 30 September 2015 and R4000 for later
registration, deadline 31 October 2015. Of this, R500 is a non-returnable
registration fee. For international participants, the course fee is 400 euros
for early bird registration, and 450 euros for late registration. Of this, 50
euros is a non-returnable registration fee. Accommodation, breakfast and dinner
is not included in the course fee, but accommodation packages may be negotiated
Registration should be done online at
Enquiries may be directed to the SACEMA Research Manager, Ms Lynnemore
Scheepers, at email@example.com, or phone: +27(0)21 8082589.
Longitudinal studies constitute an important class of studies in clinical
research and arise when a response is repeatedly measured over time. This is in
contrast to a survival study where the time to an event is recorded. In the
first case the statistical analysis involves techniques for repeated measures,
while in the second case one essentially uses survival analysis. In the last
decade a combination of the two statistical techniques is becoming popular and
involves the joint modeling of survival times and longitudinal measurements.
Longitudinal data can be analyzed in the classical, frequentist framework, but
the Bayesian approach offers more flexible modeling options which could be
useful when the data structure is complex (multivariate outcomes, multiple
levels in the data, some missing data patterns, joint modeling, etc.). We will
illustrate the Bayesian approach for the analysis of such data, by means of a
great variety of examples. Examples will be analysed using
WinBUGS/OpenBUGS/JAGS and R-versions of them, but also other software will be
used. The course consists of 2 parts: Part I: introduction to the Bayesian
approach based on the newly released book Bayesian Biostatistics of Lesaffre
and Lawson and Part II: devoted to the analysis of FU studies.
The course will be oriented towards an applied audience with a good knowledge
of various regression models. Some advance knowledge of classical repeated
measurements analysis and classical survival analysis will be helpful. The
Bayesian concepts will be introduced only briefly; hence a prior course on the
Bayesian approach will certainly be helpful. The concepts will be explained on
real data examples for which either R, WinBUGS, etc. code will be provided
together with data to try out at a later time. Knowledge of R will be quite
useful for the course, but no prior knowledge of WinBUGS is assumed, although
this also would be helpful.
Closing date for early bird registration: Wednesday, 30 September 2015.
Closing date for later registration: Saturday, 31 October 2015.
DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA)
19 Jonkershoek Road Stellenbosch 7600
Tel: +27 21 808 2589; Fax: +27 21 8082586
Epidemiological update: http://www.sacemaquarterly.com