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 Schließen

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