Generalized Linear and Generalized Linear Mixed Models with R (Module 3)

day 1: binominal model (repetition LM, logistic regression, binomial model, tests, model assumtions, overdispersion, predictions); day 2: poisson model (poisson model, tests, model assumptions, overdispersion, predictions, depending on participants: zero-inflation, mixture models); day 3 GLMM (including random effects, Bayesian way of fitting a model, glmer-function and MCMCglmm-finction, depending on participants: introduction to WinBUGS and further mixture models); day 4: projects (work on own data and presentations) Requirements Modul 1 and 2, basic knowledge in statistics, linear models (ANOVA) and linear mixed models