M7985 Survival analysis II

Faculty of Science
Spring 2022
Extent and Intensity
2/2/0. 4 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
doc. PaedDr. RNDr. Stanislav Katina, Ph.D. (lecturer)
RNDr. Bc. Iveta Selingerová, Ph.D. (seminar tutor)
Guaranteed by
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
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
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 models on for (un)censored life-time data;
- to implement methods of nonparametric and (semi)parametric statistical inference for (un)censored life-time data to R.
Syllabus
  • censoring a its types,
  • survival function, variance, risk, mean and median survival, mean and median residual life, point estimation, confidence intervals and bands, competing risks, cumulative incidence function,
  • 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,
  • Cox proportional hazard regresním model,
  • implementation in R,
  • examples from biology and medicine calculated in R language.
Literature
  • 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. On-line using MS Teams or full-time according to the according to the development of the epidemiological situation and the applicable restrictions.
Assessment methods
Homework, oral exam. The conditions may be specified according to the development of the epidemiological situation and the applicable restrictions.
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: every week.
Teacher's information
The lectures will take place online at MS Teams at the time of the normal lectures according to the schedule. Due to the possible low signal quality, I recommend students not to use the camera. Questions during the lecture will not be possible to ask by voice, but by chat.

The recording from the lecture will be uploaded in the IS sequentially and not in advance, so the recording will be uploaded only after the given lecture and before the next lecture. The recordnig does not have to contain a complete lecture, it is up to a teacher what to share from the record and share it with the students. What is a lecture recording? It can be a PDF of text written by the lecturer on the screen with an electronic pen during the lecture, and this can be supplemented by the voice (or voice and video) of the lecturer. Slides in PDF with TeX-ed text will always be available in the IS and will be shared only after the given lecture and before the next lecture.

Consultations about the lectures will take place through a discussion forum, where the lecturer / instructor moderates this discussion and new discussion forums established by students will not be taken into account. Discussion forums will be based on individual lectures and practicals (if the course has practicals) and about homework. Discussions by e-mail will not take place.

To obtain the credit, active participation in seminars is required (2 unexcused absences are allowed). An excused absence is considered exclusively an absence excused at the study department and uploaded into the information system in due time (within 5 working days from the date of the course). This is in accordance with the study regulations, where Article 9 paragraph (7) states that (7) The student is obliged to apologize in writing to the study department of the faculty within 5 working days from the date of the course being excused.

The course is also listed under the following terms Autumn 2010 - only for the accreditation, Autumn 2010, Autumn 2011 - acreditation, Autumn 2012, Autumn 2013, Autumn 2014, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021.
  • Enrolment Statistics (Spring 2022, recent)
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