Course syllabus for Survival analysis with applications in medicine
Överlevnadsanalys med tillämpningar inom medicin
Versions of this syllabus:
Essential data
Specific entry requirements
A Bachelor's degree or professional degree of at least 180 credits or the equivalent. The applicant must have completed a total of at least 60 credits in mathematics, statistics, and programming, of which univariate calculus, multivariate calculus, linear algebra, numerical methods, probability theory and statistics, and programming with a high-level language must be included. Proficiency in English equivalent to the Swedish upper secondary school course English 6/English B.
Outcomes
The course aims to equip the student with an understanding of fundamental concepts in survival analysis (censoring, truncation, timescales, and the hazard and survival functions) and methods for modelling time-to-event (survival) data, including a rigorous statistical formulation of the likelihoods and partial likelihoods, along with the competence, skills, and judgement to appropriately apply such methods in biomedical research.
Upon completion of the course, the student should be able to:
Regarding knowledge and understanding
- Define key concepts in survival analysis, including censoring and truncation, and explain the relevance of these concepts for the analysis of time-to-event data in biomedical research.
- Understand the concept of timescales in statistical models for time-to-event data.
Regarding competence and skills
- Estimate and compare survival functions and state probabilities using parametric and non-parametric methods, including testing for and modelling time-varying effects.
- Propose a suitable statistical model for assessing a specific research hypothesis using data from a time-to-event study, fit the model using standard statistical software, evaluate the fit of the model, and interpret the results.
- Be able to control for different timescales using standard statistical software, and argue for an appropriate timescale for a given research hypothesis.
- Understand how to assess discrimination and calibration for predictions based on time-to-event models.
Regarding judgement and approach
- Critically evaluate the methodological aspects (design and analysis) of a scientific article in biomedicine reporting a time-to-event study.
Content
Both theoretical and practical (hands‐on data analysis) components will be included. The following topics will be included:
- Concepts in survival analysis (censoring, truncation, timescales, and the hazard and survival functions)
- Non-parametric estimation and testing of survival functions
- Parametric models, including Poisson regression
- The Cox proportional hazards model
- Flexible parametric models
- Accelerated failure time models
- The proportional hazards assumption and how models can be extended to include time-varying coefficients (and time-varying covariates)
- Competing risks and an introduction to multi-state models
- Risk set sampling, including the case-cohort and nested case control study designs
- Discrimination and calibration
- Frailty
- Survival analysis with recurrent events
- Non-collapsibility and choice of causal effect measures
Teaching methods
The primary teaching methods will be lecture-based learning, technology-enhanced learning (primarily computer-based data analysis), individual learning, and group learning. The course focuses on active learning, i.e., putting knowledge into practice and critically reflecting upon the knowledge.
Examination
The examination consists of assignments (with written and/or oral presentation) and an individual written examination. The deliverable elements of the assignments (e.g., holding an oral presentation or submitting a written report) are to be completed before the end of the course according to the times specified in the schedule.
Compulsory participation
It is compulsory to attend the introduction to the course and the sessions in which the assignments are presented/discussed. The examiner assesses if and, in that case, how absence from compulsory components can be compensated. The student must participate in all compulsory parts or compensate for absence in accordance with the examiner's instructions, in order to pass the course. Absence from a compulsory activity may result in the student not being able to compensate the absence until the next time the course is given.
Limit to the number of examinations
A student who does not pass an examination at their first attempt is entitled to participate in five additional examination sessions. If the student does not pass after four examinations, he/she is recommended to retake the course at the next regular course occasion, and may, after that, participate in two more examination sessions. If the student has failed six examinations, no additional examination sessions are provided.
Physically attending or otherwise commencing an examination is regarded as an examination session. Handing in a blank exam is considered taking part in an examination session. An examination, for which the student registered but did not participate, is not counted as an examination session.
Adaption of examination
If there are special grounds, or a need for adaptation for a student with a disability, the examiner may decide to deviate from the syllabus' regulations on the examination form or the possibility of supplementation or exemptions from compulsory sections of the course. Content and learning outcomes as well is the level of expected skills, knowledge and abilities may not be changed, removed, or reduced.
Other directives
The course language is English.
