Table of contents

The course is connected to the following study programs

Recommended previous knowledge

  • 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

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 and learning 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.

Examinations

Individual 5-days home examination. The examination will be assessed as pass/fail.
Last updated from FS (Felles studentsystem) Oct. 15, 2026 10:25:29 AM