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 semester has meetings once a week during a whole semester (see the Course Schedules for precise details). Both semesters 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”. Each technique could be encountered in academic, clinical and corporate (research) environments. The course aims to provide foundations in a wide range of different techniques, to train methodological experience and flexilibity in many fields.
The examples and exercises will rely heavily on the R software suite (with or without R-studio); basic knowledge and understanding is advised. A short introductory module is provided to cover the bare minimum.
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.
Exercises to gain hands-on experience with the techniques in each topic.
The timetables are available through My Timetable.
Mode of instruction
Semester I (Fall):
10 two-hour lectures
10 two-hour (computer) workgroup sessions
Semester II (Spring):
12 two-hour lectures
11 two-hour (computer) workgroup sessions
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 (75%) and the weighted average of the assignments (25%). 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.
Digital Syllabus Applied Multivariate Data Analysis – Fall semester, and announced online reading materials.
Digital Syllabus Applied Multivariate Data Analysis – Spring semester.
NOTE As of the academic year 2021-2022, you must register for all courses in uSis.
You do this twice a year: once for the courses you want to take in semester 1 and once for the courses you want to take in semester 2.
Registration for courses in the first semester is possible from July. The exact date on which the registration starts will be published on the website of the Student Service Center (SSC)
Registration for courses in the second semester is possible from December. The exact date on which the registration starts will be published on the website of the Student Service Center (SSC)
The registration period for all courses closes five calendar days before the start of the course.
By registering for a course you are also automatically registered for the Brightspace module and for the first sit of the exam of that course. Anyone who is not registered for a course therefore does not have access to the Brightspace module and cannot participate in the first sit of the exam of that course.
Also read the complete registration procedure
Students have to enroll for each elective course separately.
For admission requirements contact your exchange coordinator.
Fall semester Dr. Ralph C. Alexander Rippe
Spring semester: to be announced.