spring 2020 HEL-8030 Applied Linear Regression Analysis - 3 ECTS
Application deadline
PhD students and students at Student Research program at UiT The Arctic University of Norway go directly to Studentweb to register for class and exam by 1 February.
Other applicants: Application deadline is 1 December. Application code 9303 in Søknadsweb.
If granted admission to the course you have to register for class and exam in Studentweb by 1 February.
Admission requirements
PhD students, students at a Student Research Program or holders of a Norwegian master´s degree of five years or 3+ 2 years (or equivalent) may be admitted.
PhD students not admitted to UiT The Arctic University of Norway must upload a document from their university stating that there are registered PhD students. This group of applicants does not have to prove English proficiency and are exempt from semester fee.
Holders of a Master´s degree must upload a Master´s Diploma with Diploma Supplement / English translation of the diploma. Applicants from listed countries must document proficiency in English.
Course overlap
If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:
HEL-8001 Multivariable Linear Regression Analysis and Analysis of Variance Including Repeated Measures Design 1.5 stpHEL-8027 Regression Analysis 3 stp
PSY-8012 Regression analysis 3 stp
MED-8003 Regression analysis 1 stp
Course content
The course includes correlation as well as simple and multiple linear regression analysis, with application to medical and psychological areas. In particular, the following topics are being covered:- 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
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.
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)
- About the course
- Campus: Tromsø |
- ECTS: 3
- Course code: HEL-8030
- Responsible unit
- Institutt for samfunnsmedisin