Statistics Module 2: Linear Models and Linear Mixed Models with R

day 1: LM Linear Regression, multiple Regression ANOVA, ANCOVA (least-square method, parameterisation, interactions, tests (marginal and sequential), model selection, model assumptions, predictions, introduction to Bayesian data analysis); day 2: LME linear mixed models (maximum likelihood, restricted maximum likelihood, random and fixed effects, likelihood ratio test / bootstrap, random slopes-random intercept models, evt. further model types depending on the participants wishes); day 3: LME (model matrix, simulating posterior distributions of model parameters, predictions, posterior probabilities of hypotheses, preparing data for work on own data); day 4: work on own data and presentations. Prerequisite for participation: basic knowledge in statistics