This three day course will teach you advanced topics in multilevel modelling. The three-day course builds upon the contents of the other summer school course “Introduction to multilevel analysis”. It consists of three days with lectures in the morning and computer labs in the afternoon.
After taking this course, you should be able to analyse more complex multilevel model and to interpret and report the results.
This three-day course builds upon the contents of the course “Introduction to multilevel analysis”. It consists of three days with lectures in the morning and computer labs in the afternoon.
The focus of the first day is on categorical outcome data, in particular binary, ordinal and event history outcomes. It will be shown why linear multilevel models are not appropriate for such data and how multilevel generalized linear models can be used to fit this type of outcome data. Attention will be paid to estimation procedures that are available and how the intraclass correlation coefficients and proportions explained variance are calculated. Special attention is paid to the interpretation of the estimated regression weights in terms of the logits and odds ratios.
The contents of the second and third day follow.
It is expected participants have taken the course Introduction to Multilevel Analysis or a similar course with the same contents (i.e. chapters 1-5 from Hox, Moerbeek and Van de Schoot (2018). Participants are also expected to have experience with analyzing multilevel data in common software such as Mplus, SPSS, R, HLM, or MLwiN.
Hox, J., Moerbeek, M., & Van de Schoot, R. (2018). Multilevel analysis. Techniques and Applications. 3rd edition. New York: Routledge.
Book is NOT included in fee (about 45 euros)
Irma Reyersen - email@example.com