Course in event history analysis

Overall aim:

The course will give an introduction to event history analysis and focus on extended event history analyses, such as competing risk analysis and multi-state models.

Contents:

• Hazard function and survival function
• The Kaplan-Meier estimator
• Cox-regression
• Time dependent covariates
• The principle of competing risk
• Fine&Gray regression
• Multi-state data
• Data structures in extended event history analyses
• Pseudo data in event history analyses

At the end of the course, the student should have the following learning outcomes:

Knowledge

The student recognises complex event history data and set up data structures and models for extended event history analyses.

Skills

The student:

• arranges data files and performs some analyses in the statistical packages "R" or "Stata".
• understands some pros and cons of different models.

General competence

The student:

• understands the general principles of extended event history analyses.
• has a basis for work on extended event history data.