Course content

The course is part 2 of the analysis of problems that can be elucidated by quantitative data and has the same requirements for prior knowledge as part 1, but it would be an advantage if participants have a somewhat broader understanding of the general linear model than is required for participation in part 1 - PSY9170.

Learning outcome

Day 1 (5 hours): Exploratory factor analysis with emphasis on principal component analysis.

Based on a classical test psychology understanding of reliability, the relationship between concepts and indicators is discussed. Empirical evidence of uni-dimensionality and multi-dimensionality is illustrated by concrete examples. Examples of the use of principal component analysis for "data reduction" and visualization of complex relationships between observed variables are also reviewed.

Day 2 (5 hours): Exploratory factor analysis with emphasis on classical factor analysis.

Here, greater emphasis is placed on theoretical assumptions related to latent phenomena and indicators. The difference between principal component analysis and factor analysis is discussed.

Day 3 (5 hours): A brief introduction to structural modeling.

Similar issues as discussed in part 1 of the course are addressed again (multivariate models with underlying and intervening variables and control for third variables), but now with a focus on latent variables. Measurement models and causal models are analyzed in the same model (SEM).

Admission to the course

The course is aimed at Ph.d. candidates. The Department of Psychology's own Ph.d. candidates will have first priority, then Ph.d. candidates from other institutions, then other applicants.

Ph.d. candidates from The Department of Psychology register for the course via StudentWeb. Please contact the administration if you experience problems registering.

Other applications are made via this online form.

The registration period is stated in the online form and you will receive an email shortly after the application deadline if you are offered a place on the course.

Formal prerequisite knowledge

Admission to a Ph.d. program.

It is recommended that candidates have already taken PSY9170 - Qualitative Analysis I.?

Overlapping courses

Teaching

Attendance at all classes is mandatory. Maximum absence is 20%.

The analysis tools SPSS and AMOS are used for all analyses and the analyses are demonstrated by the course leader and carried out by the participants. The teaching takes place in premises where all participants have access to a computer.

See the course's semester page for the timetable.

Access to teaching

If you have completed and been approved for compulsory teaching, you are not entitled to new teaching. If you have been admitted to the course, but have not completed or been approved for compulsory teaching, you are entitled to new teaching when there is a vacancy.

Examination

Approval of the course requires participation in all lectures and written submission of an analysis of a problem that can either be based on data from your own research project or analysis of a distributed "case".

Delivered through Inspera.

Examination support material

No aids are allowed.

Language of examination

You can answer the exam in Norwegian, Swedish, Danish or English.

Grading scale

The course uses a pass/fail grading scale. Read more about the grading scale.

More about examinations at UiO

You will find further guides and resources at the web page on examinations at UiO.

Last updated from FS (Felles studentsystem) May 19, 2025 5:18:59 PM

Facts about this course

Level
PhD
Credits
2
Teaching
Spring and autumn
Examination
Spring and autumn
Teaching languages
  • English
  • Norwegian