Working with "Mixed Models"
"Mixed Models" deal with data sets that contain multiple measurements of the same individuals or groups, a situation where classical statistical approaches are biased. In this course, we will begin with a summary of linear models and their limitations, and then explain "Mixed Models", their applicability and use. We will cover random intercept and random slope models in detail.
Prerequisites: Programming knowledge of R, e.g., "Introduction to R" course, and knowledge of regression models, e.g., "Introduction to Statistics" course. Some practice in ggplot2 is also welcome.
More details here.
Registration will be open from 26.04.