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Applied Multivariate Data Analysis (fall and spring)


Important Note

  • All Semester II bachelor and master psychology courses and examinations (2020-2021) will be offered in an on-line format.

  • If it is safe and possible to do so, supplementary course meetings may be planned on-campus. However, attendance at these meetings will not be required to successfully complete Semester II courses.

  • All obligatory work groups and examinations will be offered on-line during Central European Time, which is local time in the Netherlands.

  • Information on the mode of instruction and the assessment method per course will be offered in Brightspace, considering the possibilities that are available at that moment. The information in Brightspace is leading during the Corona crisis, even if this does not match the information in the Prospectus.

Admission requirements

Only open to MSc Psychology (Research) students and MSc (Research) students Developmental Psychopathology in Education and Child Studies.


The complete course Applied Multivariate Data Analysis which runs during an entire calendar year is a joint enterprise of the Institute of Psychology (responsible for the Spring semester) and the Institute of Education and Child Studies (responsible for the Fall semester). Participants can start either in Spring or Fall. The course is part of all Research Master programs in Psychology as well as in Education and Child Studies. Each part has meetings once a week during a whole semester (see the Course Schedules for precise details). Both parts consist of a series of topics each of which include “when and why to use a special statistical technique”, “how to use a special technique” and “how to interpret the results”.

AMDA topics – Fall semester: (1) principal component analysis, confirmatory factor analysis, (2) logistic regression and item response theory, (3) nonparametric regression and nonparametric principal components analysis (using optimal scaling), (4) clustering and (5) meta-analysis.

AMDA topics – Spring semester: (1) analysis plan (2) mediation and moderation, (3) predictive regression, (4) multilevel analysis and longitudinal analysis, and (5) missing data.

The treatment of each topic in the course will have a similar structure, in particular:

  • Exposition of the situations in which a particular technique should be used and why, illustrated with an example from actual research, wherever possible.

  • A summary exposition of the basic principles and the working of the technique and how it can be applied to real data.

  • Discussion of the output of computer programs designed to carry out the analyses.


For the timetables of your lectures, work group sessions, and exams, see the timetables page of your study programme. You will also find the enrolment codes here. Psychology timetables


Students need to enroll for lectures (and work group sessions). Please consult the instructions for registration.


Students have to enroll for each elective course separately.

Exchange/Study abroad

For admission requirements contact your exchange coordinator.


Students are not automatically enrolled for an examination. They can register via uSis from 100 to 10 calendar days before the date; students who are not registered will not be permitted to take the examination. Registering for exams

Mode of instruction

Semester I:
10 two-hour lectures
10 two-hour (computer) workgroup sessions

Semester II:
12 two-hour lectures
11 two-hour (computer) workgroup sessions

Assessment method

Performance will be evaluated by both a final exam and by written assignments. The exam will consist of MC questions and short essay questions. Participants work on the assignments in self-chosen pairs. The assignments consist of executing and (written) reporting on a data analysis with the technique discussed in the current topic. Each assignment will be graded. The final grade for each semester will be determined by the individual exam (60%) and the weighted average of the assignments (40%).. Both grades should be higher than 5.5 to pass the course. Any of the assignments can only be resit when the overall assignment grade is unsatisfactory (lower than 5.5).

The Institute of Psychology and the Institute of Education and Child Studies adhere to the policy of the Faculty of Social and Behavioural Sciences to systematically check student papers for plagiarism with the help of software. Disciplinary measures will be taken when fraud is detected. Students are expected to be familiar with and understand the implications of this fraud policy.

Reading list

Digital Syllabus Applied Multivariate Data Analysis – Fall semester.
Digital Syllabus Applied Multivariate Data Analysis – Spring semester.

Contact information