MED-BMS61
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;
Lecturer(s)
Contactperson for the course
dr. M.A. Jonker
Other course modules lecturer
Examiner
dr. M.A. Jonker
Other course modules lecturer
Academic year2017
Period
3  (30/10/2017 to 26/08/2018)
Starting block
3
Course mode
full-time
RemarksPeriod 3a, Monday and Tuesday
Registration using OSIRISNo
Course open to students from other facultiesNo
Pre-registrationYes
Pre-registration openfrom 01/04/2017 up to and including 02/10/2017
Waiting listYes
Placement procedureDone manually by Back Office
ExplanationDone manually by Back Office
Aims
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.
Content
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.
Levels
master

Instructional modes
Working group

Remark
Period 3a, Monday and Tuesday

Tests
Course examination
Test weight1
OpportunitiesBlock 3, Block 3