Syllabus database for doctoral courses

  • Syllabus database for doctoral courses


Swedish title Fortsättningskurs i medicinsk statistik: Regressions modeller
English title Intermediate Medical Statistics: Regression models
Course number 2738
Credits 3.0
Notes The course meets the requirements for a general science course.

Responsible KI department Institutionen för lärande, informatik, management och etik
Specific entry requirements Basic Medical Statistics (or equivalent)
Grading Passed /Not passed
Established by The Board of Doctoral Education
Established 2016-09-07
Purpose of the course The aim of the course is to introduce intermediate statistical methods and to facilitate acquirement of skills that involve hands-on data analysis using statistical software.
Intended learning outcomes After successfully completing this course students are expected to be able to: Understand the basic theory behind the statistical methods introduced in the course and to evaluate their applicability and limitations. Choose a suitable statistical model for assessing a specific research hypothesis using data from a medical science study, evaluate the fit of the model, and interpret the results. Apply the methods discussed in the course on real data.
Contents of the course The course is an introduction to more advanced statistical methods and requires that the student is familiar with the statistical concepts of descriptive and inferential statistics, and has some basic knowledge of linear regression. The course covers intermediate regression analysis, one-way and two-way analysis of variance, repeated measures ANOVA, logistic regression, and introduction to survival analysis. Concepts examined in this course include dummy variables, confounding variables, interaction between variables, influential observations and model selection.
Teaching and learning activities The course consists of lectures, group discussions and assignments solved individually and in groups. Some group discussions and exercises are compulsory.
Compulsory elements Computer based exercises, seminars, article presentations and some lectures are mandatory. The course leader assesses whether and if so, how absence can be compensated.
Examination Assessment of the intended learning outcomes by a passing grade on the computer based exercises, and active participation in the final seminar and article presentations.
Literature and other teaching material Eric Vittinghoff et al.: Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models, Second edition, Springer, 2012.
Course responsible Mesfin Tessma
Institutionen för lärande, informatik, management och etik

Contact person Karin Wrangö
Institutionen för lärande, informatik, management och etik