design matrix for mixed effects model

Hi Wade,
For a model y ~ x1 + x2 + (x1 + x2 | id)
you get the random effects design matrix via

model.matrix(~ 0 + id + (x1 + x2):id)

That will produce a dense model matrix for the random effects.
Depending on the number of levels of id and the number of observations
that matrix could be huge.  The lme4 package uses sparse model
matrices for the random effects terms, which is a key to the
performance on large problems.