NB Language of instruction is English
The research master course is taught at a level that is suitable for both research master students and PhD candidates. The course is open to Research Master students and PhD candidates. Students with a good background in elementary statistics and methods of research at the bachelor level can also apply. Other interested persons have to apply explicitly, also if they intend to follow a single topic (which is not encouraged).
The complete course Applied Multivariate Data Analysis is a joint undertaking of the Institute of Psychology and the Institute of Education and Child Studies and runs both in the spring and the fall semester. Participants can start either in the spring or the fall. The course is part of the Research Master programme (in Educational Sciences).
Each part has meetings once a week during the whole semester (see the Course Schedule for precise details), and both parts consist of a series of topics each of which includes “when and why to use a special statistical technique”, “how to use a special technique” and “how to interpret the results”.
Topics of AMDA – Fall semester include (1) logistic regression, (2) item response theory, (3) principal component analysis, confirmatory factor analysis and structural equation modeling, (4) nonparametric regression and nonparametric principal components analysis (using optimal scaling), and (5) meta-analysis.
Topics of the spring semester include (1) quasi-experimental design, (2) multilevel analysis including longitudinal analysis, (3) cluster analysis, (4) mediation and moderation, (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, where 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 (mostly SPSS, sometimes specialized software) designed to carry out the analyses.
- The participants have to hand in written work (assignments), on which grades are based. The assignment consists of a data analysis with the technique in question.
- Students will have to have a passing grade on all assignments. The final grade for each part will be an average of all individual grades. Grades can only be awarded to participants who have handed all assignments of a semester. Thus separate grades are awarded for each semester.
After completion of this course, participants should have:
- A thorough understanding of the various theories and methodological approaches (data analysis techniques included) which are commonly used in the research programs that are central to this research master (achievement level 2).
- The ability to independently formulate, perform and assess scientific research at a level suitable to preparing scientific publications (7).
- The ability to write scientific reports in English (8).
- Advanced, up to date knowledge of quantitative and qualitative research methodology (9).
“Timetable”: To be announced
Mode of instruction
- Computer labs (supervised)
- Independent study of the literature.
- Assignments during the course.
From January 1, 2006 the Faculty of Social Sciences has instituted the Ephorus system to be used by instructors for the systematic detection of plagiarism in students’ written work. Please see the information concerning fraud.
Information on Blackboard
Syllabus Applied Multivariate Data Analysis 1.
Please note that separate uSis registration is mandatory for lectures, seminars, exams and re-exams. Student who do not register, cannot attend courses or take exams.
- Registration for the lectures of the course is possible as of two months through one week before the first lecture at the latest;
- Registration for the seminars of the course is possible as of two months through one week before the first seminar at the latest.
Student must register for each exam through uSis. This is only possible until 10 calendar days before the exam. More information on exam registration
part A Fall semester
part B Spring semester
The course is a collaboration between the Institute of Education and Child Studies and the Institute of Psychology.