These are all the mixed effect model examples from two chapters of my book Extending the Linear Model with R. Each model is fit using several different methods:
I have focused on the computation rather than the interpretation of the models.
- Single Random Effect - the
pulp
data - Randomized Block Design - the
penicillin
data - Split Plot Design - the
irrigation
data - Nested Effects - the
eggs
data - Crossed Effects - the
abrasion
data - Multilevel Models - the
jsp
data - Longitudinal Models - the
psid
data - Repeated Measures - the
vision
data - Multiple Response Models - the
jsp
data - Poisson reponse model - the
nitrofen
data - Binary response model - the
ohio
data