23554a

L Introduction to Generalized Linear Mixed Models in R

Oksana Buzhdygan, Felix May, Felix Nößler

Ort: Seminarraum AG Tietjen (R212) (Königin-Luise-Str. 2 / 4)

Zeit: 21.09. - 02.10.2026; daily; 10:00 - 11:00

Erster Termin: 21.09.2026

Unterrichtssprache: Englisch

SWS: 1

Teilnehmerzahl: 14

Platzbeschränkung: Nein

Teilnahmepflicht: Nein

Module zu dieser LV:

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.