Entry requirements
Only open to Master’s and Research Master’s students from Psychology.
Description
In this course the focus will be on the analysis of categorical data. The course starts with basic theory on contingency tables and distributions for categorical data. Then from the general framework of Generalized Linear Models special cases are developed like logistic regression, multinomial logistic regression and log-linear models. Software, model selection and interpretation will be discussed for the models.
After this introduction attention shifts to models for longitudinal categorical data, where we distinguish between marginal, transitional and subject specific models.
Course objectives
On completion of the course students have knowledge on:
the theory of Generalized Linear Models (Gzlm);
applying models from the Gzlm framework to solving problems with empirical data; and
the SPSS software modules for analyzing categorical data extensions of generalized linear models for clustered data.
Timetable
For the timetables of your lectures, work groups and exams, please select your study programme in:
Psychology timetables
Registration
Course
Students need to enroll for lectures and work group sessions.
Master’s course registration
Examination
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
7 2-hour lectures and 2 2-hour computerlab meetings.
Assessment method
Two graded assignments and a written exam. The final grade is the average of the 3 grades obtained.
The Faculty of Social and Behavioural Sciences has instituted that instructors use a software programme for the systematic detection of plagiarism in students’ written work. In case of fraud disciplinary actions will be taken. Please see the information concerning fraud.
Reading list
Agresti, A. (2007). An introduction to categorical data analyis (Second Edition). Wiley.
Contact information
Dr. Zsuzsa Bakk
<z.bakks@fsw.leidenuniv.nl>