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, and is in prinicple not open to regular master students.. Students with a good background in elementary statistics and methods of research at the bachelor level may apply to take part. 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 which runs during an entire calendar year is a joint undertaking 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 the spring or the fall. The course is part of all Research Master programmes in Psychology and 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”.
Topics of AMDA – Fall semester: (1) principal component analysis, confirmatory factor analysis and structural equation modeling, (2) logistic regression, (3) nonparametric regression and nonparametric principal components analysis (using optimal scaling), (4) item response theory and (5) meta-analysis.
Topics of AMDA – Spring semester: (1) mediation and moderation, (2) quasi-experimental design, (3) multilevel analysis and longitudinal analysis, (4) missing data, and (5) cluster analysis.
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 (mostly SPSS, sometimes specialised software) designed to carry out the analyses.
Participants have to hand in assignments. The assignments consist of a data analysis with the technique discussed in the current topic.
Each assignment will be graded, and 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 in 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 a 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).
To be announced.
Mode of instruction
Lectures and workgroups, supervised
Independent study of the literature
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 – Fall semester.
Syllabus Applied Multivariate Data Analysis – Spring semester.
Via uSis. Maximum of 45 students.
Please note that one single uSis registration is mandatory for each semester.
- Registration for each semester is possible from two months through one week before the first lecture at the latest;
Students who do not register cannot attend classes or take the (re)exam.
The course is a collaboration between the Institute of Education and Child Studies and the Institute of Psychology.