In this video, I will demonstrate how to fit a linear mixed effect model.
I will discuss:
What is a mixed effect model?
Fixed effects
Random effects: grouping or clustering factor
The intercept
The slope
Organizing data
Model fitting and model comparison: AIC, BIC, LL
Checking the assumptions
Variance components: variance and mean
Intra-class correlation (ICC)