Course - Survival analysis - KLMED8019
KLMED8019 - Survival analysis
About
New from the academic year 2023/2024
Examination arrangement
Examination arrangement: School exam
Grade: Passed / Not Passed
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| School exam | 100/100 | 3 hours | A |
Course content
This course cover standard statistical methods for analysis of failure- or survival time data (Kaplan-Meier cumulative survival probabilities, Nelson-Aalen cumulative hazard estimate, and the semi-parametric Cox proportional hazard regression model). Simple calculations of cumulative survival probabilities and Nelson-Aalen estimate will be covered. For the Cox PH regression model, focus will be on application, including evaluation of inherent assumptions on the regression model, and what do if the assumptions are not met. Survival analyses techniques are appropriate to apply for all types of follow-up studies, including randomized, controlled clinical trials and population-based, prospective epidemiological studies. The Cox PH regression model is often used in studies based on data from HUNT and other public health surveys. The aim of these types of studies is often to identify risk or prognostic factors, or the interaction between different exposure factors.
Learning outcome
After successful completion of this course the student should
- have achieved theoretical knowledge on the methods and models covered by the course, including principles for estimation and hypothesis testing
- be able to choose an appropriate method or model to evaluate simple and more complex scientific questions
- be able to perform the data analyses by means of a statistical program package and be able to extract and interpret relevant information from the output from the analyses
- have knowledge of and be able to evaluate the assumptions on the applied model or method
- be able to report the results from the statistical data analyses in a scientific medical journal
Learning methods and activities
Lectures and exercises in autumn semester. Practical data analyses by means of SPSS and/or STATA.
Recommended previous knowledge
Introductory course in medical statistics (KLMED8004, MH3003 or equivalent) and course in logistic regression analysis (KLMED8014, MH3003 or equivalently) is recommended for this course. Some prior training in use of statistical software is also needed for successful completion of this course.
Course materials
Lecture notes and other learning material posted by teacher.
Textbook by Kirkwood and Sterne 2003; Essential medical statistics, second edition
Learning material may change.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| KLMED8005 | 1.5 | AUTUMN 2022 |
No
Version: 1
Credits:
3.0 SP
Study level: Doctoral degree level
Term no.: 1
Teaching semester: AUTUMN 2023
Language of instruction: English
Location: Trondheim
- Medicine
- Statistics
Department with academic responsibility
Department of Public Health and Nursing
Examination
Examination arrangement: School exam
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD School exam 100/100 A 2023-11-29 15:00 INSPERA
-
Room Building Number of candidates SL110 turkis sone Sluppenvegen 14 11 SL122 Sluppenvegen 14 1 - Spring UTS School exam 100/100 A 2024-06-07 09:00 INSPERA
-
Room Building Number of candidates SL110 hvit sone Sluppenvegen 14 2
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"