Statistics Module 3: Generalised linear models and generalised linear mixed models

Statistics Module 3: Generalised linear models and generalised linear mixed models

  • CHANGED LOCATION
  • Beginn: 10.12.2018
  • Ende: 13.12.2018
  • Vortragende(r): Dr. Fränzi Korner-Nievergelt
  • Oikostat
  • Ort: Möggingen/Radolfzell
  • Raum: MaxLounge
  • Gastgeber: IMPRS for Organismal Biology
  • Kontakt: mhieber@orn.mpg.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
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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