Survival analysis is the study of the distribution of life times, i.e. the times from an initiating event (birth, diagnosis, start of treatment) to some terminal event (relapse, death). Survival analysis is most prominently (but not only) used in the biomedical sciences. A special feature of survival data is that it takes time to observe the event of interest. A result of this seemingly innocent observation is that for a number of subjects the event is not observed, but instead it is known that it has not taken place yet. This phenomenon is called censoring and it requires special statistical methods. During the course different types of censored and truncated data will be introduced and techniques for estimating the survival function by employing both parametric and non-parametric methods will be illustrated. Also techniques for testing equality of survival functions (the log-rank test and alternatives) are discussed. Finally regression models for survival analysis, based on the hazard function (most notably the Cox proportional hazards model), will be studied in great detail. Special aspects such as time-dependent covariates and stratification will be introduced. Techniques to be used to assess the validity of the proportional hazards regression model will be discussed. The last part of the course focuses on models for multivariate survival analysis, including competing risks and multi-state models and frailty models.
Obtain knowledge on basic statistical theory in survival analysis and skills in performing survival analysis on different data-sets.
For the course days, course location and class hours check the Time Table under the tab “Masters Programme” at http://www.math.leidenuniv.nl/statscience
Mode of Instruction
Weekly 2 days of 2 × 45 min of class in the morning based on the reading material, and 2 × 45 min of practical sessions with exercises. For many of these exercises we expect you to bring a laptop with the statistical package R (http://www.r-project.org) already installed.
written exam (2/3), a written report (1/3), and a presentation (pass / no pass)
The report should describe the student’s results and the analysis of the survival data. The report should include feedback received during the 15 min presentation of the student’s results and data analysis.
Date information about the exam and resit can be found in the Time Table pdf document under the tab “Masters Programme” at http://www.math.leidenuniv.nl/statscience. The exams take place in the Snellius building, the room will be announced on the electronic billboard, to be found at the opposite of the entrance, the content can also be viewed online at:“http://info.liacs.nl/math/”:http://info.liacs.nl/math/
If the exam does not take place in the Snellius building, then an announcement will be sent via blackboard
Lecture material provided in class.
Survival Analysis: Techniques for Censored and Truncated Data. John P. Klein, & Melvin L. Moeschberger, Springer-Verlag (2nd edition. 2003)
Enroll in Blackboard for the course materials and course updates.
To be able to obtain a grade and the ECTS for the course, sign up for the (re-)exam in uSis ten calendar days before the actual (re-)exam will take place. Note, the student is expected to participate actively in all activities of the program and therefore uses and registers for the first exam opportunity.
Exchange and Study Abroad students, please see the Prospective students website for information on how to apply.
M.Fiocco [at] lumc [dot] nl
- This is an elective course in the Master’s programme of the specialisation Statistical Science for the Life & Behavioural sciences.