PSY9185 – Multilevel models

Schedule, syllabus and examination date

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Course content

In multilevel models (MLM), units of interest are nested within higher order units (children within classrooms, observations at different times within the same person), and influences can operate at and between all levels in the hierarchy. This allows MLM to give proper inferences in many scenarios where traditional approaches fail, while allowing researchers to pose questions that other statistical models cannot address.

Learning outcome

This course gives an introduction to multilevel models as useful analytical tools for social scientist. Practical exercises will focus on implementing and interpreting multilevel models using SPSS. Particular emphasis will be placed on the use of MLM to investigate longitudinal data. Familiarity with linear regression is assumed.

  • Learn to recognize whether there are dependencies in your data that might invalidate inferences in traditional statistical analyses.
  • Learn to implement multilevel models in SPSS, and interpret and present the results.


This is an elective course in the PhD-programme in psychology. Candidates from PhD-programmes at other institutions are welcome to apply to the course. 


Recommended previous knowledge


Enrollment in a PhD-programme.


Each spring. 


2 credit points for attendance over three days.

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

Explanations and appeals

It is recommended to request an explanation of your grade before you decide to appeal.


Appeal against grades

Complaint about formal exam errors


The deadline to request an explanation is one week after the grade is published. For oral and practical examinations, the deadline is immediately after you have received your grade.

The explanation should normally be given within two weeks after you have asked for it. The examiner decides whether the explanation is to be given in writing or verbally

Facts about this course






Every spring

Teaching language