Mixed Models

Course description

Requirements:

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).

Your profit:

The participants will be taught the limits of linear regression in the case of repeated measurements. A new model class called “mixed models” will be explained, which is able to deal with repeated measurements. Besides discussions on the interpretation and theory also ideas how to run the models with R and exercises will be provided.

Topics:

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

Methods:

The course consists of theoretical lessons on mixed models, how to apply and how to interprete mixed models. Theoretical lessons will be followed by hands-on examples with best-practice solutions in R.

  • This course will be offered either on campus (in person), or online. The dates of online and on campus courses are indicated in the table here.
  • For on campus courses please check the restrictions and hygiene rules described here*.
  • For online courses we use the software Zoom, for further information, please check the description here here*.

 

Duration: 2 Days

Language: English

Materials:

  • Material for the course can be found here*.
  • Please install the necessary R-packages prior to the course. The packages are listed in "Materials_MixedModels.html" which is part of the linked ZIP-folder.
  • Please be aware that the materials will be updated shortly before the next course.

Dates and Application:

 

 * Links marked with * are only available for HMGU staff.