I currently am fitting a mixed model on a data set of n=20,000 and my model takes the following form
So we have a random intercept and slope for each
x_4 group, and a random intercept for each
x_3 takes one of 18 values,
x_4 takes one of three values, and
x_5 takes one of 20,000 values.
I am able to fit
mask_model in a few minutes. However when I attempt to extract the random effects from this model via
ranef(mask_model) my computer just hangs. This strikes me as strange as I would think when I make the original
glmer() it would calculate these random effects. If I exclude the random intercept involving
x_5, or if I make
x_5 only take one of 5000 values then
ranef() seems to work.
Would greatly appreciate any insight into why this might be happening and a potential workaround.
I receive the following output from summary(mask_model)
When I run getME(mask_model, "b") I get a 8625x1 vector, (I have 8619 id's and 3 provinces). It appears to be that this is the conditional mode of the random effects, but ideally I could somehow extract what the id random effect is for each participant, and the random slope/intercept for each province (if that is possible; unfortunately ranef(mask_model) just hangs in R).