Introduction to mixed models in R

Users from all professional groups who have basic knowledge in statistics and have used R before. (For introductory R courses please revisit the course list.)

• CHF 600 for members of UZH/ETH and associated institutes
• CHF 800 for members of other universities, federal and cantonal research facilities and agencies, non-profit organisations etc.
• CHF 1,200 for companies, banks, insurance companies etc.

This two day course with exercises will focus on fitting and interpreting mixed models in R, using the lme4 package.

• Refresher: regression, (generalized) linear models, models for ordinal data
• When to use mixed models: data structures, repeated measures
• Why mixed models: regularization, plausibility, generalizability
• Definition & theory of mixed models
• Visualizing longitudinal & hierarchical data
• Fitting models with lme4: syntax & helper functions
• Inference with lme4: fixed effects, random effects, predictions
• Model evaluation with lme4: model criticism, model selection
• Troubleshooting: missingness patterns, non-convergence

Basic familiarity with R syntax and some experience with data analysis in R (loading data, fitting models, using the built-in graphics functions). Familiarity and some practical experience with regression modeling.

Participants should bring their own laptop with an up-to-date version of R with packages lme4, RLRsim, ordinal, ggplot2, and HSAUR installed. The RStudio IDE is recommended as well.