
I want to use a parametric bootstrap on a GLMM to to determine parameter bias (http://www.bris.ac.uk/cmm/team/hg/bias-correction.pdf) and hopefully to estimate effect confidence intervals (http://glmm.wikidot.com/faq).

I'm using glmmPQL{MASS} since I need to include an AR1 correlation structure, but there are no existing parametric bootstrap routines for this. I'm writing my own, but am coming unstuck when trying to simulate a response from the model:

m1<-glmmPQL(y ~ trt , random = ~ 1 | ID, correlation=corAR1(form=~week), family = binomial, data = bacteria)
simulate(m1)

	Error in simulate.lme(m1) : 
  		Models with corStruct and/or varFunc objects not allowed.

I'm trying to write my own simulation code by modifying that from lme4 [getMethod('simulate',signature='mer')]. I'm not sure if or how I should be including the correlation structure though, and guess there's a very good reason why simulate.lme doesn't work with a corStruct.

If anyone can give me an idea of how to simulate samples from a glmmPQL object with a corStruct, or if it's possible, then I'd be very grateful. Or just a way of obtaining a rough estimate of the bias would be great. Would a non-parametric bootstrap be completely out of the question here (e.g. http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-bootstrapping.pdf)?

Thanks,

Andrew 

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