SFOK15012U Survival and Event History Analysis
MSc in Public Health Science
The course introduces statistical concepts and methods for analyzing time-to-event (survival) data obtained from following individuals until a particular event occurs, or they are lost to follow-up. We will illustrate the use of modern tools for time-to-event analysis and discuss interpretation and communication of results. The course provides practical experience with real health science data.
The content includes: censoring and truncation; Kaplan-Meier estimation; log-rank tests; Cox regression; additive hazards models; model checking by cumulative martingale residuals; competing risks; correlated event times.
After completing the course the student is expected to:
Knowledge
- Distinguish methods for analysis of time-to-event data from other types of measurements.
- Understand the concepts of censoring and truncation.
- Explain central survival analysis concepts such as hazard, survival and cumulative incidence and their relationships.
- Describe and compare models for time-to-event data. Illustrate how the models can be applied to epidemiological or public health data.
- Understand and recognize common pitfalls specific to time-to-event data.
Skills
- Determine the proper statistical method to address a specific scientific question from a given time-to-event data set. This includes understanding the underlying assumptions of the method and identifying violations of these.
- Perform time-to-event analysis with modern techniques using statistical software. Assess the fit of the model.
- Interpret the results reported by statistical software. Communicate the results and conclusions of a time-to-event analysis in a clear and precise way.
- Write a statistical report with a well-defined problem statement, method and result presentations, discussion and conclusion.
- Critically read and review reports or articles addressing epidemiological and public health questions by time-to-event analysis.
Competencies
- Identify and conceptualize questions encountered in the professional life of a public health researcher that can be addressed by time-to-event studies.
- Independently design, carry out and communicate time-to-event studies.
- Give advice and take active part in collaborations where decisions are based on the statistical analysis of time-to-event data.
- Category
- Hours
- Class Instruction
- 20
- Exam
- 25
- Preparation
- 93
- Total
- 138
- Credit
- 5 ECTS
- Type of assessment
- Written assignmentProject report at the end of the course.
- Exam registration requirements
Participants are required complete a minimum of 80% of the home assignments.
- Aid
- All aids allowed
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
- Exam period
- Re-exam
Criteria for exam assesment
Knowledge
- Distinguish methods for analysis of time-to-event data from other types of measurements.
- Understand the concepts of censoring and truncation.
- Explain central survival analysis concepts such as hazard, survival and cumulative incidence and their relationships.
- Describe and compare models for time-to-event data. Illustrate how the models can be applied to epidemiological or public health data.
- Understand and recognize common pitfalls specific to time-to-event data.
Skills
- Determine the proper statistical method to address a specific scientific question from a given time-to-event data set. This includes understanding the underlying assumptions of the method and identifying violations of these.
- Perform time-to-event analysis with modern techniques using statistical software. Assess the fit of the model.
- Interpret the results reported by statistical software. Communicate the results and conclusions of a time-to-event analysis in a clear and precise way.
- Write a statistical report with a well-defined problem statement, method and result presentations, discussion and conclusion.
- Critically read and review reports or articles addressing epidemiological and public health questions by time-to-event analysis.
Course information
- Language
- English
- Course code
- SFOK15012U
- Credit
- 5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Spring And Block 4
- Schedule
- See the Schedule in Syllabus
- Course capacity
- 30 students
- Study board
- The Study Board for Public Health Science and Global Health
Contracting department
- Department of Public Health
Course responsibles
- Frank Eriksson (8-707d74767e7e7a794b7e80796f397680396f76)