Application deadline

External applicants: Application deadline is 1 December for Spring semester and 1 June for Autumn semester. Application code 9303 in Søknadsweb.

If granted admission to the course you have to register for class and exam in Studentweb by 1 February in Sring semester and 1 September in autumn semester.

PhD students and students at Medical Student Research program at UiT The Arctic University of Norway go directly to Studentweb to register for class and exam by 1 February in Spring semester and 1 September in Autumn semester.

Type of course

Admission requirements

PhD students, master students at a Medical Student Research Program, or holders of a Norwegian master´s degree of five years or 3+ 2 years (or equivalent) may be admitted. Valid documentation is a statement from your institution that you are a registered PhD student or master student at a Medical Student Research Program, or a Master´s Diploma with Diploma Supplement / English translation of the diploma. PhD students are exempt from semester fee.

For information about how to apply for admission, go to: http://uit.no/helsefak/forskning/phd/emner

Course content

• Model selection  procedures
• Interaction and confounding
• Regression diagnostics
• Transformation of variables
• Fractional polynomial regression
• Regression splines
• Power analysis
• Implementation of these techniques in statistical software packages

Recommended prerequisites

Objectives of the course

After taking the course, the students should

know about

• the general linear model, its assumptions and applications
• the concept of model selection and significance testing
• how a power analysis can be usefully applied

be able to

• identify different types of explanatory variables and correctly implement them in a linear regression model.
• select the most appropriate model to study the relationship between one or more explanatory variables and one continuous response variable.
• assess interaction and confounding variables.
• interpret the results from linear regression models.
• evaluate whether the assumptions of the regression models are fulfilled.
• calculate power and sample size in linear models

have the general ability to

• evaluate results from publications in medical/psychological journals where linear regression models are applied, and critically assess the validity of their use.

Language of instruction and examination

Teaching methods

Assessment

Written assignment (10-20 pages) to be submitted. Evaluated as passed / failed.

The course is held annually. There will not be arranged a re-sit exam for this course.

Recommended reading/syllabus

Recommended literature:

Kleinbaum, Kupper, Nizam & Rosenberg: Applied Regression Analysis and Other Multivariable Methods. Duxbury (2013), fifth edition

Andy Field: Discovering Statistics Using IBM SPSS Statistics. Sage (2013), fourth edition

Field, Miles, Field: Discovering Statistics Using R. Sage (2012)