Analysis and Design of Studies with Repeated Measures
ME-629-1
Included in Study
PhD Programme in Health and Sport Sciences
Recommended pre-requisites
EX-602 Philosophy of Science
ME-626 General Quantitative Research Methods, ME-428 or corresponding courses
Learning outcomes
On successful completion of the course, the candidate has:
Knowledge about
can evaluate on an advanced level strength and limitations with respect to repeated measures designs
knows pros and cons of statistical software for mixed models
can interpret missing data in analysis
Skills
can critically reflect regarding strengths and limitations with respect to repeated measures design
can perform repeated measures analysis
can critically reflect on strengths and limitations of the repeated measures statistical models
General competence
can independently plan, analyze, report and interpret own analysis of data from repeated measures design
can interpret and critically analysis from repeated measures design from published research
Course contents
Advanced with respect to repeated measures designs
Regression towards the mean
Hawthorne-effect
Paired samples t-test
Regression analysis
Reflections with respect to choosing the most appropriate model
Different statistical software’s for mixed models
Teaching methods
Lectures combined with practical statistical exercises in a computer lab. Examples of analysis of data will to a great degree be connected to the faculty’s on-going or planned research projects.
Examination requirements
Participation in compulsory lectures as stated in the course pamphlet.
Assessment methods and criteria
Individual 5-days home examination. The examination will be assessed as pass/fail.