[R-sig-ME] Parametric bootstrap for mixed models

[Douglas Bates]

I have been considering how to provide functions for the parametric
bootstrap applied to mixed models.  That is, take an lmer model,
simulate new responses for a model with this specification and the
parameters at the estimated parameter values, then obtain the value of
some statistic for a model fit to the new data.

It occurs to me that it would be best to split this operation into two
stages, one to simulate data from a fitted model and a second which
takes a fitted model, new data and a function to apply to the updated
model.  The reason it seems best to split write this as two functions
or methods is because you may want to simulate from one model (the
null model) and fit another model (the alternative) to get the value
of the statistic.

Does this seem a reasonable approach or am I likely to paint myself
into a corner doing this?  Is anyone sufficiently familiar with some
of the packages that do bootstrapping to offer an alternative model?

If I do things this way, the first function can be a method for the
simulate generic.  Any suggestions of what to call the second one?