Huub van den Bergh, University Utrecht
Sven De Maeyer, University Antwerp
Dates and location: (10:00-17:00 hours):January 27-29, 2021, Utrecht (location to be determined)
Researchers often face situation where data are gathered on different observational units. A classical example from educational research involves the investigation of the impact of school characteristics on the performance of the students. In such a case students are nested within schools. Another example often encountered in educational research are studies with the same subjects measured on multiple occasions (e.g. pre-test/post-test designs, or longitudinal designs). Hence, observations are nested within subjects. Failing to take the hierarchy of data into account during analysis will result in over-optimistic parameter estimates. That is, the null-hypothesis is rejected to easily. Multilevel analysis, or more generally mixed modelling, provides a solution to the problems with this kind of hierarchical or nested data.In this course you will learn to perform multilevel analyses. We will start from a very basic multilevel model and elaborate this model to accommodate research designs with a pre-test post-test design, and models with random-cross-classifications. For this workshop we expect the participants have SPSS (18+) installed on their laptop. In the course theory and hands-on exercises are mixed-up in such a manner that theoretical explanations can be applied directly in a realistic research situation. We assume that participants are familiar with statistical procedures like anova and regression analysis.
* SPSS 18 or higher needs to be installed on your laptop