PřF:M7985 Survival analysis - Course Information
M7985 Survival analysisFaculty of Science
- Extent and Intensity
- 2/2/0. 4 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: zk (examination).
- doc. PaedDr. RNDr. Stanislav Katina, Ph.D. (lecturer)
Mgr. Bc. Iveta Selingerová, Ph.D. (seminar tutor)
- doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Department of Mathematics and Statistics - Departments - Faculty of Science
Contact Person: doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Supplier department: Department of Mathematics and Statistics - Departments - Faculty of Science
- Mon 18. 2. to Fri 17. 5. Mon 8:00–9:50 M2,01021
- Timetable of Seminar Groups:
- 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 the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- The main goal of the course is to become familiar with some basic principles of statistical analysis of events in time to (1) understand and explain basic principles of nonparametric and (semi)parametric statistical inference and statistical modelling for (non)censored data; (2) implement these techniques in R language; (3) be able to apply them to real data.
- Learning outcomes
- Student will be able:
- to understand principles of likelihood and nonparametric statistical inference and (semi)parametric statistical models for (un)censored life-time data;
- to build up and explain suitable nonparametric statistical test and (semi)parametric for (un)censored life-time data;
- to apply nonparametric statistical inference and (semi)parametric statistical modelson for (un)censored life-time data;
- to implement methods of nonparametric statistical inference for (un)censored life-time data to R.
- censoring a its types,
- survival function, variance, risk, mean and median survival, mean and median residual life, point estimation, confidence intervals and bands
- testing of statistical hypotheses – comparisons of two or more survival curves, relative risk, nonparametric principles for censored data,
- generalisation of correlation coefficients in testing of hypotheses about survival curves,
- implementation in R,
- examples from biology and medicine calculated in R language.
- KLEIN, John P. and Melvin L. MOESCHBERGER. Survival analysis : techniques for censored and truncated data. 2nd ed. New York: Springer, 2003. xv, 536. ISBN 9781441929853. info
- Teaching methods
- Lectures, practicals.
- Assessment methods
- Homework, oral exam.
- Language of instruction
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/spring2019/M7985