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Høst 2020
HEL-8003 Mixed Models - 2 stp
The course is administrated by
Type of course
Course contents
During the course the following topics are discussed:
- Basic principles of multilevel analysis
- Background of multilevel analysis
- Example of a multilevel analysis with a two level structure
- Example of a multilevel analysis with a three level structure
- Multilevel analysis with dichotomous outcome variables
- The use of multilevel analysis in longitudinal studies
- Generalised estimating equations
- Alternative models for longitudinal data analysis
- Sample size calculations
- Missing data
- Software for mixed models
Application deadline
Registration deadline for PhD students and students at the Medical Student Research Program at UiT - The Arctic University of Norway: September 1st
Application deadline for other applicants: June 1st. Application code 9303 in Søknadsweb.
Admission requirements
Objective of the course
Having attended the course and completed the exam the students will obtain the following learning outcomes:http://www.nokut.no/en/Facts-and-statistics/The-Norwegian-Educational-System/The-Norwegian-qualifications-framework/Levels/
(National Qualifications Framework 1st, 2nd & 3rd cycle)
Knowledge and understanding:
- Understand the basic principles of multilevel analysis.
- Understand the difference between mixed models with continuous, binary and count outcomes.
- Understand the difference between longitudinal analyses with continuous, binary and count outcomes.
- Understand generalised estimating equations (GEE) models.
- Interpret results from mixed models and GEE models.
- Know how to handle missing data in mixed models and GEE.
Skills:
- Be able to use a statistical package to analyse data using mixed models and GEE models.
- Perform sample size calculations for mixed model analysis and for longitudinal studies.
- Separate between the different correlations structures in GEE models
General Competence:
- Know how to interpret results from mixed models and GEE models.
- Know about different softwares for mixed models and GEE models.
Language of instruction
Teaching methods
Assessment
Home Exam. Evaluated with passed/failed.
The course will be arranged irregularly and no continuation exams will be given.
Date for examination
The date for the exam can be changed. The final date will be announced at your faculty early in May and early in November.