Advanced statistics: general linear mixed models 2018

26. November, 9:00 bis 3. Dezember 2018, 17:30 Uhr

IGB, Müggelseedamm 310, lecture hall

Die Anmeldefrist für die Veranstaltung ist leider abgelaufen.

This course is suitable for anyone with a solid understanding of basic statistics and well-practiced use of R


Please note that this course is rather intense and that you cannot do much besides it. Participants are expected to participate in the entire course!

In this course, you will learn about the proper application of mixed models to account for random effects, such as repeated or nested measures, in Gaussian data. The course will cover conceptual model building and practical applications using R. You will learn when it is necessary to include random effects, how to check that model assumptions are being met, and model validation. We will additionally touch on how these techniques can be generalized to non-Gaussian data, such as count, binary, and binomial data.

Topics include:

  • Refresher on linear regression and their interpretation
  • Repeated measures data and accounting for temporal auto-correlation
  • Nested (hierarchical) versus nested random effects
  • Random regression models (random intercepts & slopes)


This course will require a comfortable understanding of basic statistics including linear regression. The course will comprise lectures and hands-on student work. In addition, all students will be required to work in a group to perform and present a detailed analysis of a data set. This data set can be of the student’s own (if appropriate) otherwise an example data set will be provided. The course will be taught exclusively in R and it is required that all students have a comfortable knowledge of basic R commands.



Take your statistics knowledge to a higher level and bring your own data!


26.11-03.12. all day (9:00-17:30)


26.-28. Nov: Lectures and exercises


29.-30.-Nov Group work on real data


03. Dec: presentation of group work and open questions 

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