PřF:E8678 Applied survival analysis - Course Information
E8678 Applied survival analysis
Faculty of ScienceAutumn 2024
- Extent and Intensity
- 2/0/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- doc. Mgr. Zdeněk Valenta, M.Sc., M. S., Ph.D. (lecturer)
RNDr. Tomáš Pavlík, Ph.D. (lecturer) - Guaranteed by
- RNDr. Tomáš Pavlík, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Tomáš Pavlík, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Wed 12:00–15:50 F01B1/709
- Prerequisites
- Bi5045 Biostatistics for Computational Biology
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Biomedical bioinformatics (programme PřF, N-MBB)
- Epidemiology and modeling (programme PřF, N-MBB)
- Course objectives
- The aim of this course is to introduce the main concepts of survival analysis and basic statistical methods and models for evaluation of survival data. Students learn to understand survival data and their most common shortcomings, learn how to construct the most widely used estimates and models evaluating the impact of variables on time to the occurrence of an event of interest. The course focuses on practical applications rather than on mathematical theory and proofs.
- Learning outcomes
- At the end of the course, students are able:
- to understand the basic concepts of survival analysis,
- to define the survival function and the risk function and know the functional relationships between them,
- to know the basic probability distributions of survival data,
- to construct common estimates of the survival and cumulative risk functions including confidence interval,
- to define and validate the proportionality of risks,
- to apply Mantel-Haenszel logrank test for two groups,
- to describe advantages and disadvantages of nonparametric and parametric survival models,
- to formulate, explain and use proportional risk models, accelerated failure time model, Aalen's additive model and Gray's flexible model with time varying regression coefficients,
- to understand the meaning of model regression coefficients. - Syllabus
- Basic terms in survival analysis
- Nonparametric estimates
- Parametric estimates
- Methods for comparing survival functions
- Relative survival
- Regression models in survival analysis
- Cox proportional hazards model
- Aalen's additive model
- Gray's flexible time-varying coefficients model
- Literature
- recommended literature
- KLEIN, John P. and Melvin L. MOESCHBERGER. Survival analysis : techniques for censored and truncated data. New York: Springer, 1997, xiv, 502. ISBN 0387948295. info
- MARUBINI, Ettore and Maria Grazia VALSECCHI. Analysing survival data from clinical trials and observational studies. Chichester: John Wiley & Sons, 1995, xvi, 414. ISBN 0471939870. info
- Teaching methods
- In-person classroom attendance and lecturing, class discussion, group project
- Assessment methods
- one written test (30 questions, each contributing 1 point, 25 points needed to pass), final (group) project, oral examination in case of failing the written test.
- Language of instruction
- Czech
- Further Comments
- The course is taught annually.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/autumn2024/E8678