E8678 Applied survival analysis

Faculty of Science
Autumn 2024
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
In-person direct teaching
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
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
Study Materials
The course is taught annually.
The course is also listed under the following terms Autumn 2022, Autumn 2023.
  • Enrolment Statistics (recent)
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