Notes & Code

Lectures
Lecture 1 - Introduction to fixed and random effects
Lecture 2 - Random intercepts and slopes (R script)
Lecture 3 - Simulating fixed and random effects data (R script, Assignment 1 (PDF file))
Lecture 4 - Repeated-measures designs (R script, ZIP file of data)
Lecture 5 - Partially-hierarchical designs (R script, mcgoldRM data)
Lecture 6 - Multiple comparisons and mixed models (R script, we'll use the wines.txt datafile, load the multcomp package)

Workshop 1: Fixed effects versus random effects
Workshop 1 R script
the RIKZ data
Zuur et al's book website 
Get the data used in Zuur's book (.zip file) 
Faraway's book website
Install the faraway package on your computer (use Package Installer)
Get all the data from Crawley's R Book

Workshop 2: Running a simple mixed effects model
Workshop 2a R script - testing hypotheses in mixed models
Install the nlme package (using Package Installer)
Install the lme4 package (using Package Installer)
Get Faraway's PDF updating his treatment of the lme4 package

Workshop 3: Fully nested model case study
Install the faraway package
Workshop 3a: Nested models and variance components (R script, hre data)
Workshop 3b: How to simulate fully nested data (R script)
Assignment 2 (PDF file, Aquilegia data)
The R-Forge site for lme4
Draft chapters of Douglas Bates' book on lme4

Workshop 4: Repeated-measures models
Workshop 4 (R script)
Assignment 3 (PDF file)

Workshop 5: Evaluating significance in LMMs
Install the pbkrtest package
Install the boot package
Install the car package
Install the lmerTest package
Install the RLRsim package
Workshop 5 (R script)
Assignment 4 (PDF file, Decodon ID data)

Workshop 6: Reporting mixed model results
Install the lmerTest package
Install the lsmeans package
User guide for the lsmeans package
Workshop 6: presenting mixed model results (R script)
Rhinanthus pollen limitation data
The published result: Hargreaves et al. 2014 J. Ecol.