Deakin University (Burwood Campus, Melbourne) are hosting a statistics course entitled “Introduction to Linear Mixed Effects Models and GLMM with R: Bayesian and frequentist approaches”. It will be lead by Dr. Alain Zuur & and Dr. Elena Ieno, and will run from the 4 - 8 July, 2016.
The course starts with a basic introduction to linear mixed effects models, followed by an introduction to Bayesian statistics, MCMC and generalised linear mixed effects models (GLMM) to analyse nested (also called hierarchical or clustered) data, e.g. multiple observations from the same animal, site, area, nest, patient, hospital, vessel, lake, hive, transect, etc.
During the course several case studies are presented, in which the statistical theory for mixed models is integrated with applied analyses in a clear and understandable manner.
Throughout the course MCMC is executed in JAGS (free software) via the package R2jags from within R. Bayesian and frequentist (lme4, nlme, glmmADMB) analyses are compared.