Statistical modeling in observational research
Course infoSchedule
Course moduleMED-BMS61
Credits (ECTS)3
CategoryMA (Master)
Language of instructionEnglish
Offered byRadboud University; Faculty of Medical Sciences; Biomedische wetenschappen;
dr. M.A. Jonker
Other course modules lecturer
Contactperson for the course
dr. M.A. Jonker
Other course modules lecturer
dr. M.A. Jonker
Other course modules lecturer
P. Vart
Other course modules lecturer
Academic year2019
W44-A  (28/10/2019 to 31/08/2020)
Starting block
Course mode
RemarksMonday and Tuesday for 4 weeks after the start of the period.
Registration using OSIRISYes
Course open to students from other facultiesYes
Pre-registration openfrom 01/04/2019 up to and including 14/10/2019
Waiting listYes
Placement procedureDone manually by Back Office
ExplanationDone manually by Back Office
The main objectives of this module are:
Upon completing this course the student should be able to:
  1. Choose an appropriate multivariable statistical technique to analyze data gathered in the context of medical scientific research.
  2. Perform multivariable regression analyses with the aid of the computer package R/SPSS, interpret the results, and report the conclusions.
  3. Describe (roughly) the statistical background of some multivariable analysis techniques that are frequently applied in medical scientific research.
The module 

To a large extent, medical research is aimed at identifying associations between two variables. For example, we may be interested in the association between an independent variable treatment and a dependent variable survival. However, in most cases there are other variables that act as confounders of an observed association and have to be taken into account. Although we are not directly interested in the confounders, they (partially) explain the relationship between the explanatory and outcome variables. It is important to take potential confounders into consideration in order to properly understand the association between the variables that we are interested in. This course considers techniques that correct for potential confounders and provide a valid statistical interpretation of confounded relationships. Confounding can be controlled for analytically, using either stratified analyses or through the use of multiple regression techniques. The regression approaches considered in this course are also used when one is interested in the relationship between one variable (the dependent variable) and a number of other explanatory variables considered simultaneously. Multivariable analysis methods are very useful, particularly in the context of observational epidemiological research. The statistical package R or SPSS is used for the practical training of those techniques.

Presumed foreknowledge

Test information


Instructional modes
Working group

Written exam
Test weight60
Test typeWritten exam
OpportunitiesBlock W44-A, Block W44-A

Written report
Test weight40
Test typeReport
OpportunitiesBlock W44-A, Block W44-A