Analysis of longitudinal and correlated data
Ph.D. -course
- ECTS credits
- 2
- Teaching semesters
- Autumn
- Course code
- MEDSTA3
- Number of semesters
- 1
- Resources
- Schedule
Course description
Course content
Improve the ability of health researchers to analyses correlated data
Learning outcomes
Knowledge
After completion of the course the student should be able to:
- Perform analyses of longitudinal data where each unit of observation is observed several times
- Know about methods for analysis of data with correlation between observations like data from cluster-randomized studies
- Know alternatives with robust estimation of variances, random intercept and GEE
Skills
After completion of the course the student should be able to:
- Analyze data with simple correlation structures
- Restructure data from wide- to long-format
- Perform relevant regression analyses with the statistical software Stata
General skills
After completion of the course the student should be able to:
- Understand when statistical analyses need to account for systematic correlation between observations
Language of instruction
English
Pre-requirements
Recommended Previous Knowledge
Own research experience
Form of assessment
Home examination
Pass/Fail
Who may participate
PhD
Supplementary course information
The students are required to have Stata available on their own computer, preferably a laptop that can be used during the course and for home work.