Introduction to mixed models in R

Lecturer Fabian Scheipl, Institute for Statistics, University of Munich
Duration 2 days
Certificate Certificate of attendence
Target
audience

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.)

Costs
  • 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.
Course
language
English/German (depending on the composition of the participants)
Course
description

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
Prerequisites

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.

Dates Thursday June 4th and Friday June 5th 2015
Registration deadline: 21.05.2015