[R-sig-ME] ¿Can I do an internal validation of glmer()? ¿By glmer() -> corrected AUC optimism by bootstraping technic bootMer() [internal validation of a mixed-effects-model]?

[Andreu Ferrero]

¿ Can I do an internal validation in a mixed-effect-model?

Here is some code:

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> 
> 
>> 
>> 
>> 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)
library(boot)
>> 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 
>> **************************************************************************************************************************************
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