Statistics Module 2: Linear Models and Linear Mixed Models with R
Statistics Module 2: Linear Models and Linear Mixed Models with R
- Beginn: 05.12.2016
- Ende: 08.12.2016
- Vortragende(r): Dr. Fränzi Korner-Nievergelt
- Oikostat
- Ort: Möggingen/Radolfzell
- Raum: MaxLounge
- Gastgeber: IMPRS for Organismal Biology
- Kontakt: mhieber@orn.mpg.de
Linear models (LM) and linear mixed models (LME):
Linear Regression, multiple Regression, ANOVA, ANCOVA, model selection (group work), linear mixed models, work on own data
- least-square method
- parameterisation
- interactions
- tests (marginal and sequential)
- model assumptions
- predictions
- introduction to Bayesian data analysis
- posterior distributions
- maximum likelihood, restricted maximum likelihood
- random and fixed effects
- likelihood ratio test / bootstrap
- random slopes-random intercept models
- possibly further model types depending on the participants wishes
- model matrix
- predictions, posterior probabilities of hypotheses
- preparing data for work on own data
Prerequisite for participation: basic knowledge in statistics
Course material 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.