sponsored by Helmholtz Information & Data Science Academy (HIDA)

in cooperation with Core Facility Statistical Consulting  at Helmholtz Zentrum München - German Research Center for Environmental Health (HMGU)

Mixed Models

“Mixed Models” address datasets containing multiple measurements of the same individuals or of groups, a situation in which classical statistical approaches are biased. In this course, we begin with a summary of linear models and their limitations, then explain “Mixed Models”, their applicability, and usage. We will cover random intercept and random slope models in detail.

Prerequisites: Programming skills with R, e.g. course “Introduction to R” and knowledge of regression models, e.g. course “Introduction to Statistics”. Some practice in ggplot2 is also welcome.

More details here.