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
Statistics Module 3: Generalised linear models and generalised linear mixed models
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
Day 2: Poisson model
  • Poisson model
  • model assumptions, overdispersion
  • tests, predictions
  • depending on participants wishes: zero-inflation
Day 3: GLMM
  • including random effects
  • glmer-function
  • depending on participants wishes: introduction to WinBUGS and more complex models
Day 4: projects
  • 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.

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