[R] Bootcov for two stage bootstrap

[tonitogomez]

Dear users,

I'm trying to implement the nonparametric "two-stage" bootstrap (Davison and
Hinkley 1997, pag 100-102) in R. As far as I understood, 'bootcov' is the
most appropriate method to implement NONPARAMETRIC bootstrap in R when you
have clustered data (?). I read the 'bootcov' manual but I still have a few
questions:

1 - When the variable 'cluster' is introduced, then only clusters will be
resampled (with replacement)?

2 - I can implement 'two-stage' bootstrap in STATA by running bootstrap
sampling on top of the bootstrap command.  Example:  bootsrap cost,
cluster(group): bsampling cost treat 
This means that in the 1st stage I resample clusters (with replacement) and
then resample individuals within those clusters.

I wonder whether we could do a similar procedure in R, i.e. if it is
sensible to do something like:

f<-boot(cost~treat)
mod<-bootcov(f, cluster, B=1000, coef.reps=TRUE)

Do you have any other ideas? Do I need to define 'fitter'?

Thanks a lot,

Manuel Gomes


-- 
View this message in context: http://n4.nabble.com/Bootcov-for-two-stage-bootstrap-tp1819605p1819605.html
Sent from the R help mailing list archive at Nabble.com.