Student Seminar in Statistics

Topic: Survival Analysis

Description:

Time to event data play an important role in applications in reliability and survival studies. In this seminar, we discuss techniques to analyse such data, paying attention to both theoretical and applied aspects.

Prerequisites:

As prerequisites, we require:

• Introductory course to statistics
• Basic knowledge of the software R (www.r-project.org)

Terms and conditions:

Each student is required to hold a presentation about a given subject (2 to 3 students per class and they must rotate during the presentation). Additionally, the presence in the seminar classes is mandatory. After each seminar class a homework set consisting of questions regarding the subject of the presentation(s) will be assigned to a random selection of students. The homework has to be handed-in at the beginning of the following class in written form (at least a reasonable attempt at solving the questions is expected).

Two weeks prior to the presentation date each student has to attend a meeting with the responsible assistant (see schedule) to discuss the topic and ask open questions. It is expected that the student has already read the material and is familiar with the topic. These meetings will take place either on Monday morning or Tuesday morning (time and place have to be fixed with the assistant directly).

One week prior to the presentation at the start of class each student has to hand in their presentation (PDF/PPT or copy of hand-written notes in case of black board presentation) and their hand-out (PDF/DOC).

Guidelines:

We strongly recommend to use our guidelines while preparing your presentation. Also consider the following points:

• Interact with the audience by asking questions, e.g. a poll or simple TRUE/FALSE questions, and encourage questions from the audience;
• Use examples and visual aids - they will help the audience to understand your argument;
• In the schedule for your presentation plan a discussion at the end (5 - 10 minutes).

Literature:

• Survival analysis: A self-learning text, Kleinbaum D.G. and Klein M., Springer 2005. Chapters 1-9 (ebook link) (classes 1-6, 9-11)
• Information Bounds and Nonparametric Maximum Likelihood Estimation, Groeneboom P. and Wellner J.A., Birkhäuser 1992. Part II, chapters 1.1, 4.1 and 5.1 (class 8)
• Cox Proportional-Hazards Regression for Survival Data, Fox Companion, Fox J. (download PDF, R code and data set) (class 7)
• Survival Analysis in R, Diez D. (link) (class 7)
• Computation of the MLE for bivariate (interval) censored data, Maathuis M. (download PDF) (class 12)
• Klein, John P., and Melvin L. Moeschberger. Survival Analysis: Techniques for Censored and Truncated Data. New York: Springer, 2003. (more mathematical book)

Program:

The schedule can be found here. After the first seminar class the corresponding names will be added to the schedule.

Frequently Asked Questions:

If you still have questions regarding your presentation please read our FAQ.

Slides and Synopsis:

1. Introduction to Survival Analysis
2. Kaplan-Meier Survival Curves and the Log-Rank Test
3. The Cox Proportional Hazards Model and Its Characteristics
4. Evaluating the Proportional Hazards Assumption
5. The Stratified Cox Procedure
6. Extension of the Cox Proportional Hazards Model for Time-Dependent Variables
7. The Cox Model in R
8. Nonparametric estimation for interval censored data
9. Parametric Survival Models
10. Recurrent Event Survival Analysis
11. Competing Risks Survival Analysis
12. Beyond Cox Models in R