Event-history analysis, fall 2008
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.
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).
Computer class exercises (room C128)
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
http://www.rni.helsinki.fi/~kja/melanoma.pdf A background article for course work 4.
http://www.rni.helsinki.fi/~kja/Bonemarrow.pdf How to compute (non-parametric) cumulative incidence functions.
The data sets:
http://www.rni.helsinki.fi/~kja/diet.dat data for course work 1
http://www.rni.helsinki.fi/~kja/mouse.dat data for course work 2
http://www.rni.helsinki.fi/~kja/smallpox.dat 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.
- 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.