1. Linear Mixed Modelling Using R
Francis Duah
Maths Skills Centre,
Academic Support Office

2. Session Outline When to conduct Linear Mixed Modelling
Differences between Linear Regression Modelling and Linear Mixed Modelling in R
Packages for conducting Linear Mixed Modelling in R
Formatting Repeated Measures Data for Analysis in R
What are Random Effects and Fixed Effects
Interpretation of the Linear Mixed Model Output from R

3. Resources for your ongoing learning
Gardeners Own
The R Basics You Need to Know before Doing Linear Mixed Modelling
University of Western Sydney
Data Analysis and Visualisation in R
Advanced topics in R
Harvard University Data Science Services
Regression Models and Multilevel Models in R
Technical University of Denmark
Analysis of correlated data in R

4. Excel Files to Copy
Filenames
clinicaltrial.csv
placebostudy2.csv

5. Packages for Linear Mixed Modelling in R
Must include
lme4
lmerTest
car

6. Modelling
What are Fixed Effects and Random Effects

7. Fixed Effects and Random
Random Effects
Gender
One age versus another
Drug treatment administered or not
Wet versus Dry
Insecticide sprayed or not
Nutrient added or not
One country versus another
Light versus shade
Individual
Parent
Household
Block within a field
Split plot within a field
Genotype

8. Modelling Fit Linear mixed models with Varying Intercept
Fit Linear mixed models with Varying Slope
Fit Linear mixed models with Varying Intercept and Slope
Interpret the Linear Mixed Model Output from R

9. Practical – Demonstration
Goal: To develop a LINEAR MIXED model TO INVESTIGATE THE EFFECT OF TREATMENT/ INTERVENTION ON OUTCOMES
Fit a Linear Mixed Model to “clinical trial” data

10. Practical – Exercise or Homework
Goal: To develop a LINEAR MIXED model TO INVESTIGATE THE EFFECT OF TREATMENT/ INTERVENTION ON OUTCOMES on
Fit a mixed linear model to “Placebo Study Two”

11. Assumptions of Linear Mixed Modelling
Check these by plotting residuals, the fitted values and the predicted random effects.
Check these by plotting residuals, the fitted values and the predicted random effects.
The covariance matrix does not dependent on the group
The random effects are independent in different groups
Within groups errors are independent of the random effects
Within groups errors are independent with mean zero and variance

12. Take Home Message Practice and practice with authentic research data.
Seek advice from your supervisor.
Consult the Maths Skills Centre at the earliest opportunity.
Attend our PG Statistics Workshops.

13. Thank You for Listening
Keep in touch
Francis Duah
Maths Skills Centre,
Academic Support Office