Course Topics

This course will discuss the concept of random effects, why they are called random effects and how they are incorporated in the framework of mixed models. The primary focus of the course will be to identify scenarios where a mixed model approach will be appropriate. We will discuss several examples with various types of response and experimental designs. The course will also talk briefly about what is a hierarchical model and why they are the obvious choice of modelers in most cases. This will be followed by an example that explicitly defines a hierarchical structure. The concepts will be explained almost wholly through examples in SAS or in R.

The course will be open for questions and discussion at the end. Feel free to ask questions specific to your research and if your data will benefit from a hierarchical structure or a mixed model.