Course content

Application deadline for this course is 1 February. Here is Application form. This is an intensive one-week course to take place in May or June. The course gives a deeper understanding of the commonly used first generation multivariate analysis techniques in psychological research as well as in other fields of the social sciences. The course first treats thoroughly multiple regression analysis which also includes dummy-variable regression (ANOVAs), moderation analysis or interaction effects (Factorial ANOVAs) and mediation analysis. We then go through logistic regression and exploratory factor analysis (principal component and common factor). Further, we show how one can use the multilevel framework to analyse repeated measures and longitudinal data. The main software to be used during the course is STATA and R. The course gives a theoretical introduction to the various analysis techniques, followed by lab exercises under supervision.

Learning outcome

Knowledge:

The candidate...

• has deep theoretical and practical knowledge of the first generation multivariate quantitative methods that are commonly used in psychological and social science research.
• has knowledge of the assumptions for applying these methods in addition to the ability to appropriately assess the methods used to the corresponding research questions.

Skills:

The candidate...

• has the ability to transform theoretical research problems into hypotheses that can be tested through methods that are taught in the course.
• has the skill to set up an analytical strategy based on theory and knowledge of methodology.

General Qualifications:

The candidate...

• has expertise in quantitative research and has knowledge of how research results can be communicated in scientific publication format.
• has the expertise to be able to evaluate published psychological research from a methodological viewpoint.

Learning methods and activities

Participation in lectures and lab exercises. The course consists of 30 hours and is arranged over a period of five days. The form of assessment is an individual paper of 4000-5000 words.

Submission deadline approx. 1. October. There is no teaching in the autumn semester. The paper will be assessed by using the passed/not passed grading option. The paper should demonstrate that the candidate has been able to employ one or several of the techniques treated in the course. The candidate can use primary and/or secondary data.

An identical version of the exam paper cannot be used directly in the PhD thesis as an article or a chapter. A revised version of the exam paper may be included in the thesis.

The course is offered when at least five PhD candidates are registered.

Compulsory assignments

• Participation in lectures and exercises

Recommended previous knowledge

Basic knowledge of quantitative social research and of statistics is recommended. Furthermore, experience with statistical software such as SPSS, STATA, R etc. may be useful.

Required previous knowledge

Completed Master's degree or equivalent. The course is limited to a maximum of 25 candidates. Candidates admitted to a PhD programme have priority.

Ranking

1. Candidates admitted to a PhD program at NTNU
2. Candidates who can document admission to a PhD program at other institutions
3. Other applicants

Course materials

Recommended literature will be sent to the participants before the course starts.