Course description

• Course content
• Learning outcome
• Admission
• Prerequisites

• Overlapping courses
• Teaching
• Examination
• Evaluation

Course content

The aim of the course is to make the participants familiar with statistical regression methods frequently applied in epidemiology. This will make participants a better equipped for following the increasing part of epidemiological and medical literature making use of such methods. The course will also form a basis for applying such methods in one¡¯s own work.

Learning outcome

Knowledge 
After completing the course, you will be able to:  

• Explain/describe results from regression analyses in the medical literature.  
• Explain/describe the assumptions made, and limitations of, regression models.
• Explain/describe in what situations to apply different types of regression models. 

Skills 
After completing the course, you will be able to: 

• Run regression analyses in one¡¯s own work. 
• Assess the adequacy of fitted regression models.  
• Interpret estimates resulting from regression models. 

General competence 
After completing the course, you will be able to: 

• Reflect upon the assumption needed for using regression models. 
• Judge what type of analyses that is adequate for different types of data and problems. 
• Appreciate the role of regression models in health research.

Admission

This course is only available for master students at Folkehelsevitenskap og epidemiologi (FHE), and International Community Health (ICH). Students at FHE and ICH must apply for this course in Studentweb.

• Students at Folkehelsevitenskap og epidemiologi have priority
• There are 10 available seats for students at International Community Health. If there are more than 10 applicants from International Community Health, the principle of the first come, first served applies.

Prerequisites

Recommended previous knowledge

• INTHE4020 ¨C Introduction to Quantitative Methods; or equivalent.
• INTHE4021 ¨C Introduction to Epidemiology; or equivalent.

Overlapping courses

4 credits overlap with MF9510 ¨C Logistisk regresjon, overlevelsesanalyse og Cox-regresjon (continued)

Teaching

The course consists of lectures, exercises and discussions.

Examination

Home exam.

Grading

The Board at the University of Oslo has decided to introduce detailed guidelines for all examinations, which take place at the University. The description of the grading should be clear and transparent. This is done to ensure alignment between learning outcomes, assignments, and grading. The Faculty of Medicine has developed a web page with information regarding exams and the grading procedures. 

Submit assignments in Inspera

You submit your assignment in the digital examination system Inspera. Read about how to submit your assignment.

Use of sources and citation

You should familiarize yourself with the rules that apply to the use of sources and citations. If you violate the rules, you may be suspected of cheating/attempted cheating.

Language of examination

The examination text is given in English.You may submit your response in Norwegian, Swedish, Danish or English.

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

Explanations and appeals

• Explanation of grades and appeals

Resit an examination

• Illness at exams / postponed exams
• Resitting an examination

Withdrawal from an examination

It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.

Special examination arrangements

Application form, deadline and requirements for special examination arrangements.

Evaluation

The course is subject to continuous evaluation. At regular intervals we also ask students to participate in a more comprehensive evaluation.