Entry requirements

120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science.

Learning outcomes

A student who has gone the course should

- have a basic theoretical and practical understanding of Structural Equation Models (SEM)

- be able to apply SEM on real problems

- have ability to interpret and present the results.

- be able to estimate structural equation models with maximum likelihood and least squares and be able to evaluate the results.

Content

The course deals with the logical and the statistical theory of SEM. The practical use of models and methods as a research aid within the social and behavioural disciplines. The course covers modern statistical aspects on regression analysis, exploration and confirmative factor analysis, and general structural equations with and without latent variables for one or more groups.

The course deals with estimation methods for structural equation models based on various types of data: normal distributed ordinal data. Robust estimation methods.

Instruction

Lectures and computer exercises.

Assessment

The examination takes place in the form of a written exam, assignments and presentation of scientific articles.

"If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator."