glmer() -> corrected AUC optimism by bootstraping technic bootMer() [internal validation of a mixed-effects-model]

I would like to do an internal validation of a discriminative ability of a mixed effects models.

Here is my scrip:

###########################
####bootMer-> boot AUC#####
###########################

library(lme4)
library(lattice)
data(cbpp)

#fit a model

cbpp$Y<-cbpp$incidence>=1
glmm<-glmer(Y~period + size + (1|herd), family=binomial, data=cbpp)
glmm

##### funcio: versio 3 - no cal posar endpoint en la funcio
##########################################################



AUCFun <- function(fit) {
 library(pROC)
 pred<-predict(fit, type="response")
 AUC<-as.numeric(auc(fit at resp$y, pred))
}


#test

(AUCFun(glmm))

###run bootMer: AUCFun



system.time(AUC.boot <- bootMer(glmm,nsim=100,FUN=AUCFun,seed=1982, use.u=TRUE,
                               type="parametric", parallel="multicore", ncpus=2))


#...

(boot.ci(AUC.boot, index =c(1,1), type="norm"))

roc(cbpp$Y, predict(glmm, type="response"))


#Now it seems more reasonable, bias as "optimism"... but still do not know #if I am just doing a AUC with bootstrap CI 
**************************************************************************************************************************************