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Description: Essentially all statistical problems can be formulated as regression problems: the ...
Archive 2015
Introduction: Description: Essentially all statistical problems can be formulated as regression problems: the problem of quantifying the relationship between a dependent variable and one or more independent variables. Surprisingly many statistical problems encountered in clinical practice can be succesfully handled with a small set of "core regression techniques", alongside an understanding of the rationale and limitations of statistical regression in general. The present course is a case-based introduction to these core regression techniques, with an emphasis on common features rather than differences.
Topics covered will include the following:
- Linear regression (including the t-test)
- Analysis of variance
- Logistic regression
- An introduction to Cox regression for survival data
The course includes computer practical exercises. Upon completion of the course, the student will be able to perform basic regression analyses in a suitable statistical software program. The student will also obtain a broad foundation for learning and applying other and more advanced regression techniques.
Literature: To be announced
Prerequisites: Knowledge of statistics (including confidence intervals and P-values), at the level of the PhD course "Quantitative research methods: an introductory guide for clinicians".
Evaluation: Written assignment
Organizer: Anders Gorst-Rasmussen, PhD, senior biostatistician
Lecturers: To be announced
ECTS: 2.4 (3 days)
Time: 4., 11. 18 June 2015
Place: Forskningens Hus, Sdr. Skovvej 15, 9000 Aalborg, room 106
Zip code: 9000
City: Aalborg
Number of seats:
Deadline: 15 May, 2015