Analysis of longitudinal and correlated data

Ph.D. -course

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
Basic knowledge on regression methods and familiarity with Stata is required, similar to HELSTA/MEDSTA + MEDSTA2 and MEDSTATA
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.