After this 2-day course, participants should
-understand the basics of multi-level modelling including its principles and assumptions
-know different applications of MLM
-know when to use MLM
-be able to perform MLM in a standard statistical software.
-be able to interpret and explain the results of multilevel models clearly
Multilevel models are designed to explore and analyse data that come from populations which have a complex structure. Behavioural and social data commonly have a nested structure. Multilevel models are becoming an increasingly popular method of analysis for situations where responses are grouped, such as in schools or other institutions, neighbourhoods, firms, parliamentary constituencies, or any other social or spatial clusters. A particular version of multilevel modelling is where there are multiple measures on each respondent, so that the grouping is of measures within person; where these multiple measures are taken on successive occasions, multilevel modelling provides a means of modelling individual change over time. This course will emphasise the practical application of multilevel models and lectures will be combined with practical sessions in order to reinforce concepts.
Course contents
Flash presentation on application of MLM in participant’s own research or field (5-10 minutes each)
The evaluation will be based on compulsory attendance, exercises during the practice sessions and the flash presentation.
Target group
The course is intended for post-graduate candidates and researchers who are interested in the use of multi-level modelling in their research. Understanding of basic statistics is required.
Enrolment: At the maximum 24 students. Priority will be given to those who need MLM in their research (PhD researchers most especially).
For pre-selection evaluation, please write a short text stating: