The course is connected to the following study programs

Recommended prerequisites

  • EX-602 Philosophy of Science

  • ME-626 General Quantitative Research Methods, ME-428 or corresponding courses

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

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

Examination requirements

Participation in compulsory lectures as stated in the course pamphlet.

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.

Assessment methods and criteria

Individual 5-days home examination. The examination will be assessed as pass/fail.

Last updated from FS (Common Student System) July 1, 2024 1:54:46 AM