Inference and prediction for life and health processes
The course treats models of survival data with two or more states, and inference and prediction for these types of models.
The course includes the following:
- Analysis of censored and truncated data from life and health processes
- Parametric and nonparametric estimation of survival functions and life length distributions
- Methods for comparing and testing survival curves from several populations
- Parametric och semi-parametric regression models of survival data
- Parameter estimation for multistate models
- Predictive modeling of future mortality and sickness
The course consists of two parts, theory and project work.
Teaching Format
Teaching consists of lectures and supervision of project work.
Assessment
Assessment of Part 1 Theory takes place through written examination, and for Part 2 Project work through oral and written hand-in of project work.
In order to pass the course, you must pass both the theory part and the project work.
Examiner
A list of examiners can be found on
The schedule will be available no later than one month before the start of the course.
We do not recommend print-outs as changes can occur. At the start of the course,
your department will advise where you can find your schedule during the course.
Note that the course literature can be changed up to two months before the start of the course.
Aalen, Borgan and Gjessing (2008) Survival Event History Analysis: A Process Point of View. Springer.
Course reports are displayed for the three most recent course instances.
