TILM3578 Statistical Methods in Epidemiology (6 cr)
Cooperation network course
Network: Cross-institutional studies in advanced courses in mathematics and statistics
This course is offered through the Network for Advanced Studies in Mathematics. These studies are available for the following degree students:
- Bachelor's Degree Programme in Mathematics
- Master's Degree Programme in Mathematics
- Bachelor's Degree Programme in Mathematics (Subject Teacher)
- Master's Degree Programme in Mathematics (Subject Teacher)
- Bachelor's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Master's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Doctoral Programme in Mathematics and Statistics
- Doctoral Programme in Mathematics and Science (Specialication in Mathematics)
Grading scale:
0-5
Description
Risk; odds; hazard; measures of relative risk; odds ratio; hazard ratio; cohort studies; case control studies; logistic regression; Poisson regression; confounding; matching; stratification; interaction and effect modification; Cox proportional hazards model.
Learning outcomes
The student will learn the basic concepts related to modelling risk in epidemiological studies. The student can build regression models to estimate the effects of different exposure variables on health outcomes. The student can address the problem of confounding in the analysis of observational data. The student can choose an appropriate study design and conduct and interpret the statistical analyses within the chosen framework.
Additional information
The course will be taught jointly for students majoring in statistics and students from other disciplines. The next round of the course will take place in 2025. The course is taught in English.
Description of prerequisites
The course is suitable for students in other disciplines, provided that the student has some previous familiarity with statistical modelling, in particular in the fields of epidemiology and medicine.