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Event-history analysis, fall 2008


Kari Auranen
Sangita Kulathinal


6-8 cu.


Advanced studies.


Basic skills in statistics and programming.


Weeks 36-38, September 1-5, 8-10, 15-16 from 09.00 to 13.00.

Place: September 1, 2, 4, 5, 8, 9, 15, 16 room B120; September 3, 10 room C323. Computer class exercises in room C128.

Lecture summaries

Friday (Sep 5): See Course works below.

Monday (Sep 8): Please read articles by Bull et al. ("Tutorial in biostatistics") and Andersen (Competing risks). The links to these articles you can find below.

Wednesday (Sep 10) : Please read articles by Andersen and Keiding (Sections 1, 2, 3, 4, 5.1.1, 5.1.2, and 5.6) and Hougaard (Sections 1, 2 and 5.3). (Tuesday, Sep 16)

Computer class exercises (room C128)

Discussion articles

Bull and Spigelhalter: Tutorial in biostatistics
Andersen: Competing risks as a multi-state model
Andersen and Keiding: Multistate models for event history analysis
Hougaard: Multi-state models: a review

Course works A background article for course work 4. How to compute (non-parametric) cumulative incidence functions.

The data sets: data for course work 1 data for course work 2 data for course work 3
The data set for course work4 is available in R.


Andersen, P. K., Borgan, O, Gill, R. D., Keiding, N. Statistical Models Based on Counting Processes. Springer-Verlag, (1993).

Kalbfleisch, J. D., and R. L. Prentice. The Statistical Analysis of Failure Time Data. 2nd ed. New York: Wiley, (2002).

Per Kragh Andersen and Niels Keiding. Multi-state models for event history analysis. Statistical Methods in Medical Research 2002; 11: 91-115.

Per Kragh Andersen, Steen Z Abildstrom, Susanne Rosthøj. Competing risks as a multi-state model. Statistical Methods in Medical Research 2002; 11: 203-215.


There will be one exercise class every day illustrating event history analysis using R.

Course content

  • Monday (Sep 1) Introduction to survival and event history analysis. Practical I (Intro to R and basics to survival analysis in R).
  • Tuesday (Sep 2) Estimation of survival functions and the construction of likelihood functions. Parametric survival distributions. Practical II.
  • Wednesday (Sep 3) Parametric, semiparametric and nonparametric inference in survival models. Practical III.
  • Thursday (Sep 4) Model checking, stratified analysis. Practical IV.
  • Friday (Sep 5) Introduction to course works. Practical V.
  • Monday (Sep 8) Discussion article I (Choice of time scale,open and closed cohorts etc.).
    Discussion article II (Competing risks).
  • Tuesday (Sep 9) Discussion article III (Event history analysis). More on event history models. Practical VI.
  • Wednesday (Sep 10) Counting process formulations. Practical VII.
  • Monday (Sep 15) Special topics (late entry, truncation, cross-sectional sampling etc.). Practical VIII.
  • Tuesday (Sep 16) Bayesian analysis of survival models. Practical IX.

Registration at the first lecture.

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