|Survival and event history analysis I||5 Cr||Luentokurssi||28.10.2019 - 11.12.2019|
|Survival and event history analysis I||5 Cr||Luentokurssi||11.3.2019 - 29.4.2019|
Master's Programme in Mathematics and Statistics is responsible for the course. The course belongs to the Statistics and Social statistics study tracks.
The course is available to students from other degree programmes and it is in the teaching curriculum of the Master´s Programme in Life Science Informatics. The course is also suitable for doctoral students and exchange students and for Bachelor´s level statistics studies as an optional course.
Edeltävät opinnot tai edeltävä osaaminen
Probability theory, statistical inference, generalized linear models and programming with R
The course gives theoretical as well as practical insight into analysis of time to (one) event. The course also builds up to more complex settings of multi-state models.
Recommended time/stage of studies for completion: 1. or 2. year
Term/teaching period when the course will be offered: usually Period II
The course first introduces the basic concepts such as type of data, censoring mechanisms and tool in standard survival analysis. Topics covered are
• survival, hazard (risk of failures), and cumulative hazard functions
• parametric models (exponential, gamma, Weibull distributions)
• nonparametric inference (Kapln-Meier estimator) of survival
• parametric (Weibull), semi-paramtertic (Cox model) and nonparametric (Poisson regression) regression models
• competing risks model
• counting processes and compensators
• introduction to models with multiple states and many possible transitions between the states are then considered. Special emphasis is given to the likelihood construction under such event-history models.
Each lecture is complemented with an R practical in the computer class, covering examples from various discipline. During the course, a number of review and research articles with different application areas are discussed.
Exercises and exam. The type of the exam will be discussed during the first lecture.
Lecture notes and articles to be announced during the course
Arviointimenetelmät ja -kriteerit
Between 1 to 5 (best)
The course has lectures, weekly discussions and exercises, and a course work at the end. The course is subject to continuous evaluation. The lecturer also asks students to participate in discussion and exercise sessions for more comprehensive evaluation. Students will submit weekly exercises and also write a short (max. 1 page) learning diary to compensate for not participating in the discussion.
4 hours of lectures/exercises per week.
The lecturer may change the course to self-study with supervision if three or fewer students attend the class.