please bring an USB drive to class this week and the following.
if you prefer to use your own machine, do standard r-install or r-studio.
Watch the 8 min talk (hit the big green button).
1) what is the difference between a GLM and a GLMM?
GLM: only has fixed effects
GLMM: has fixed and random effects
both have: a set distribution and associated link function, response variable not assumed to be linear or normal, response variable should be continuous, explanatory variables are categorical and can have continuous covariates
2)What is the difference between fixed and random effects?
Fixed: this is the treatment in your experiment, should have an effect on your response (slope changes)
Ex: soil characteristics are the fixed effect when testing the influence of soil on plant growth of different species
Random: intercept changes but should not have an effect on your response (slope does not change)
Ex: species is a random effect when testing the influence of soil characteristics on plant growth of different species
3) Checklist of steps for running a GLM/GLMM (Box 4 Bolker)
4) Common errors that are made when performing a GLM/GLMM
Selecting the wrong distribution and/or the wrong link function
not checking the fit of the model to the distribution
Here are some examples of meta-analyses and systematic reviews from my lab to get a sense how simple they can be (that’s how we roll).