Course ObjectiveAfter this course, the students will understand the basic principles of
multilevel analysis and longitudinal data analysis. Furthermore, they
will be able to perform these techniques with standard software
packages. Specific goals are that:
• The student is able to explain and apply multilevel analysis for
• The student is able to explain and apply the basic principles of the
advanced techniques for longitunial data.
• The student is able to explain the differences between different
methods and models of analysing clustered data and to motivate a choice
for one of these models in the context of epidemiological datasets/
• The student can interpret results from the various methods and models
in the context of epidemiological datasets/ research examples
• The student is capable of performing the advanced techniques using
various software programs
• The student can deliver an oral presentation following a scientific
format on a data-analysis assignment involving correlated data focusing
on the data-analyses, results and conclusion.
• The student can write the data-analysis, results and conclusion
section of a short scientific paper demonstrating he/she is able to
reflect on the results of the advanced analyzing techniques
Course ContentIn the lectures several aspects of advanced methodology for correlated
data will beintroduced and discussed. In the computer practical, these
methods will be applied using several software packages; SPSS and
Stata. In the last part of the course, the students will
receive a dataset and will have to answer a research
question based on the data provided. The results of their analyses
should be reported in a 'short' paper consisting of a statistical
analysis, results and discussion
Teaching MethodsLectures (7 times 3 hours)
Computer practical (6 times 3 hours)
Research assignment (3 times 3 hours)
Oral presentation (1 time 3 hours)
Preparing and writing a scientific paper
Method of AssessmentWritten exam (70%)
Oral presentation (0%; formative test)
The written exam and the paper must have been graded at least a 5.5.
Entry RequirementsStudents must have knowledge of epidemiology and 'standard' linear,
logistic and Cox-regression analysis.
Literature- Sheets of the lectures
- Twisk JWR. Applied longitudinal data analysis for epidemiology. A
practical guide. Cambridge University Press, Cambridge, UK, 2003.
- Twisk JWR. Applied multilevel analysis. A practical guide. Cambridge
University Press, Cambridge, UK, 2006
Target AudienceThis course is aimed at students from the Msc Health Sciences. Students
from other Master programs can only enter the course when they can show
that they have enough back ground knowledge and skills in epidemiology
and statistics (see also under entry level.
|Language of Tuition||English|
|Faculty||Faculty of Science|
|Course Coordinator||dr. M.R. de Boer|
|Examiner||dr. M.R. de Boer|
dr. M.R. de Boer
prof. dr. J.W.R. Twisk
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Lecture, Computer lab|
This course is also available as: