Analyzing data with repeated measurements or clusters
Programming skills with R, e.g. course Introduction to R and knowledge of regression models, e.g. course Introduction to Statistics. Basic knowledge on applying ggplot2 functions is advantageous but not mandatory (e.g. course Graphics with R).
“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. Besides discussions on the interpretation and theory also ideas how to run the models with R and exercises will be provided.
This introductory course on Mixed Models covers:
- Limits of linear regression in case of repeated measurements
- Introduction of mixed models
- Random intercept models
- Random slope models
- Interpretation and application of mixed models using R
The course consists of theoretical lessons on mixed models, how to apply and how to interpret mixed models. Theoretical lessons will be followed by hands-on examples with best-practice solutions in R.
- Duration: 2 Days
- Language: English
- This course will be offered either on campus (in person), or online.
- For online courses we use the software Zoom
Dates and Application:
- Courses provided for Helmholtz Munich:
- You can check the current dates and whether the courses are already fully booked here*. The course registration will usually open 8 weeks prior to the course.
- Please read the corresponding FAQ* before applying via the forms of the HR Development department*.
- NEWS: As long as the internal registration homepage CaMS is not working, please contact Elmar Spiegel for registrations.
- Courses provided for HIDA:
* Links marked with * are only available for Helmholtz Munich staff.