Statistics Module 3: Generalised linear models and generalised linear mixed models
Statistics Module 3: Generalised linear models and generalised linear mixed models
- Beginn: 05.10.2021
- Ende: 08.10.2021
- Vortragende(r): Dr. Fränzi Korner-Nievergelt
- Oikostat
- Ort: MPIO Seewiesen, if the current regulations allow
- Gastgeber: IMPRS for Organismal Biology
- Kontakt: imprs@uni-konstanz.de
Generalised linear models and generalised linear mixed models: Binomial model, Poission model, GLMM and work on own data
NOTE: This course is planned to take place at the MPIO in Seewiesen. Short term changes to an online course or to the MPI-AB in Radolfzell are possible.
Day 1: Binomial model
- refreshing LM and LMM
- introduction Bayesian data analysis
- logistic regression, binomial model
- model assumptions, overdispersion
- tests, predictions
- Poisson model
- model assumptions, overdispersion
- tests, predictions
- depending on participants wishes: zero-inflation
- including random effects
- glmer-function
- depending on participants wishes: introduction to WinBUGS and more complex models
- work on own data and presentations
Prerequisite for participation: Modul 1 and 2, basic knowledge in statistics, linear models (ANOVA) and linear mixed models
Course material: participants are asked to bring the material of module 2, particularly the book: Korner-Nievergelt, F., T. Roth, S. Von Felten, J. Guélat, B. Almasi, and P. Korner-Nievergelt. 2015. Bayesian Data Analysis in Ecolog Using Linear Models with R, BUGS, and Stan. Elsevier, New York.