This course is designed as an introduction to mixed effects modelling. These models involve data arising from longitudinal studies or studies where the data exhibits some form of hierarchy, and sometimes referred to as multilevel modelling.
Mixed effects modelling is used when observations are not independent of each other (e.g., clustered data, repeated measures). This type of analysis is regularly used in such areas as educational research when studying the performance of students within schools and in medical research when investigating the outcomes over time following major trauma.
Mixed effects refer to the inclusion of both fixed effects (i.e., the variables that are constant across individuals) and random effects (i.e., account for variability among subjects around the relationships captured by the fixed effects).
This course will be discussing the linear mixed effects models in which the outcome of interest is continuous. Discussion of some of the uses of mixed effects models in publications will be discussed at the end of the course.
- Teacher: Joanna Dipnall