Syllabus for Analysis of Survival Data
Statistiska metoder för analys av överlevnadsdata
- 7.5 credits
- Course code: 2ST072
- Education cycle: Second cycle
Main field(s) of study and in-depth level:
Explanation of codes
The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:
- G1N: has only upper-secondary level entry requirements
- G1F: has less than 60 credits in first-cycle course/s as entry requirements
- G1E: contains specially designed degree project for Higher Education Diploma
- G2F: has at least 60 credits in first-cycle course/s as entry requirements
- G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
- GXX: in-depth level of the course cannot be classified
- A1N: has only first-cycle course/s as entry requirements
- A1F: has second-cycle course/s as entry requirements
- A1E: contains degree project for Master of Arts/Master of Science (60 credits)
- A2E: contains degree project for Master of Arts/Master of Science (120 credits)
- AXX: in-depth level of the course cannot be classified
- Grading system: Fail (U), Pass (G), Pass with distinction (VG)
- Established: 2007-01-24
- Established by: The Faculty Board of Social Sciences
- Revised: 2023-03-02
- Revised by: The Department Board
- Applies from: Autumn 2023
120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science.
- Responsible department: Department of Statistics
After completing the course, the student is expected to
- have basic knowledge of the most common methods for the analysis of survival data,
- be able to apply these methods on data from the medical field and other subject areas,
- be able to assimilate the content of scientific articles based on survival data,
- have the ability to both orally and in written form account for results of analyses based on methods for survival data.
Censuring and truncation. Hazard and survival function, cumulative incidence. Estimation of the survival function: Kaplan-Meier method, Nelson-Aalen method. Methods for comparison of two or more survival curves. Analysis of the relationship between explanatory variables and survival time (regression): Non-parametric methods especially the Cox PH model, parametric models. Methods for dealing with competing risks.
Instruction is given in form of lectures, computer exercises and/or seminars.
The examination takes place through a written examination at the end of the course and/or through oral and written presentations of compulsory take-home assignments.
The reading list is missing. For further information, please contact the responsible department.