23554a
Vorlesung
L Introduction to Generalized Linear Mixed Models in R
Oksana Buzhdygan, Felix May, Felix Nößler
Hinweise für Studierende
Additional module information: Introduction to Generalized Linear Mixed Models in R
Zusätzl. Angaben / Voraussetzungen
Prior knowledge in R and linear models including regression, ANOVA and ANCOVA is required. Please bring your own laptop with R and RStudio installed.
Kommentar
This course builds on the course Introduction to Advanced Biostatistics and covers the following topics:
- Recapitulation of linear and generalized linear models
- Introduction to Linear Mixed Models for grouped data in R
- Examples for data sets with spatially nested structure or longitudinal data with repeated measures
- Introduction to Generalized Linear Models for count, proportion and binary data
- Fundamentals of Bayesian Statistics
- Maximum Likelihood Estimation and Bayesian Inference using Markov-Chain-Monte Methods
- Zero-inflation and overdispersion in GLMMs
- Outlook on more complex hierarchical models
Literaturhinweise
Statistical rethinking : a Bayesian course with examples in R and Stan / Richard McElreath, 2020. Boca Raton ; London ; New York : CRC Press
A beginner's guide to GLM and GLMM with R : a frequentist and Bayesian perspective for ecologists / Alain F. Zuur ; Joseph M. Hilbe ; Elena N. Ieno. 2013. Highland statistics
Mixed effects models and extensions in ecology with R / Alain F. Zuur 2009. Springer
The R book / Michael J. Crawley. Wiley, 2013.
Schließen
10 Termine
Regelmäßige Termine der Lehrveranstaltung
Mo, 21.09.2026 10:00 - 11:00
Di, 22.09.2026 10:00 - 11:00
Mi, 23.09.2026 10:00 - 11:00
Do, 24.09.2026 10:00 - 11:00
Fr, 25.09.2026 10:00 - 11:00
Mo, 28.09.2026 10:00 - 11:00
Di, 29.09.2026 10:00 - 11:00
Mi, 30.09.2026 10:00 - 11:00
Do, 01.10.2026 10:00 - 11:00
Fr, 02.10.2026 10:00 - 11:00