Admission requirements
The research master course is taught at a level that is suitable for both 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.
Description
The course runs during the whole year; each semester for 16 weeks. The course consists of a series of in total 10 topics.
One part of the course, part A, starts in the first semester (September-December) of each academic year, and the other part in the second semester, part B, (January-April). Students are free to choose which part they like to start with. They may continue the second part in the next academic year. Each part consists of a series of mini-courses where each topic includes “when and why to use a special statistical technique”, “how to use a special technique” and “how to interpret the results”.
Topics include:
factor analysis and principal component analysis
nonlinear analysis of categorical data
principal components analysis
regression analysis
(multiple) correspondence analysis
multidimensional scaling & cluster analysis
longitudinal data analysis & repeated measures
logistic regression
missing data analysis (in the first semester)
applied regression & analysis of variance
quasi-experimental designs
classical test theory & item response theory
multilevel analysis
structural equation modeling in the second semester.
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.
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 (especially SPSS) designed to carry out the analyses.
The participants will have to hand assignments. The assignment consists of a data analysis with the technique in question.
Each assignment will be graded, and students will have to have a passing grade on all assignments. The final grade will be a weighted average of all individual grades. Grades can only be awarded to participants who take part in the entire course.
Course objectives
A short exposition of a variety of techniques will be given.
Students learn to choose which technique to apply in which situation.
Timetable
Applied Multivariate Data Analysis – Mini Courses in Statistics (2011-2012):
- Lectures (1st and 2nd semester)
Mode of instruction
Lectures and work groups, supervised
Assessment method
The assessment is bases on graded assignments during the course. Part A en B are graded separately.
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 .
Blackboard
Information on blackboard.leidenuniv.nl
Reading list
Capita Selecta
Master’s introduction and enrolment day
Make a reservation in your agenda so you will not miss any information that you will need during your master’s programme MSc in Psychology. Please consult the Agenda master meetings
Contact information
part A first semester
- Ralph C.A. Rippe MSc
E-mail: rrippe@fsw.leidenuniv.nl - Prof. Pieter M. Kroonenberg
E-mail: kroonenb@fsw.leidenuniv.nl
- Ralph C.A. Rippe MSc
part B second semester
- Ralph C.A. Rippe MSc
E-mail: rrippe@fsw.leidenuniv.nl - Dr. M. De Rooij
Room 3B14
Tel.: +31 (0)71 527 4102
E-mail: rooijm@fsw.leidenuniv.nl
- Ralph C.A. Rippe MSc
The course is a collaboration between the Institute of Education and Child Studies and the Institute of Psychology.