UV9210 – Path analysis and structural equation modeling

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Course content

Structural equation modeling is a multivariate statistical analysis that analyzes structural relationship. These analyses utilize regression and factor analyses to estimate relationships between observed (measured) and unobserved (latent) variables. Structural equation modelling is now an approach that is highly popular within the areas of education and psychology.
This course gives an introduction to path-analysis, confirmatory factor analysis (CFA), hierarchical confirmatory factor analysis, multi traits multi methods (MTMM), multiple group CFA with covariates MIMIC), structural equation modeling (SEM), exploratory structural equation modeling (ESEM),  longitudinal structural equation models (autoregressive, growth and change-score models), mediation, multi-group models and measurement invariance. Mplus is used to estimate the various models. The course includes practical exercises where participants can practice on a given material and thus learn the skills needed to estimate the various models themselves.


PhD candidates at the Faculty of Educational Sciences will be given priority, but it is also possible for others to apply for the course. Applicants must have at least a Master's degree.

Candidates admitted to the PhD Programme at the Faculty of Educational Sciences should apply through Studentweb

Other applicants may apply using this application form

Registration deadline: February 27, 2022.


Time: March 21-25, 2022

You will find the timetable and literature on the semester webpage for this course.


To obtain 5 study points participants need to submit a paper after the course. 80% attendance is required. 

The paper should be between 8 and 10 pages and should demonstrate the use of some of the methods presented in the course. It should contain a short presentation of the research question, a larger methods and result section, and a section where the results are discussed in relation to the research questions. The paper should preferably be based on the participant’s own data. In case the participant does not have access to own data, she or he can reanalyze data from a published article to test new or additional hypotheses. Outputs from the estimated models should be submitted as a supplement (not part of the 8-10 required pages).

Papers are to be submitted electronically in Canvas.

The deadline for paper submission: TBA

Language of examination

The papers can be written in Norwegian or English.

Grading scale

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

Facts about this course






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