[R] bootstrapping nlme fits (was boot function)

[Prof Brian Ripley]

First, this has very little to do with boot: PLEASE use an infromative
subject line.  You need to work out how to resample in this situation: are
you resampling subjects or observations?  If you are resampling subjects,
you need to create a data frame containing just the resampled subjects and
pass that to nlme.

However, you also need to think if this is valid.  If you resample 
subjects, you will be fitting subjects twice or more as if they are 
independent.  I know of no theoretical studies on resampling mixed-effects 
models, and urge you to look for such results.

On Fri, 22 Aug 2003, Brunschwig, Hadassa {PDMM~Basel} wrote:

> I skimmed through the archives and couldnt really find an answer to my
> question. 

It's not an R question.

> One thing i dont understand of the description of the function
> boot() is the second variable for statistics. I have a sample of say 19
> subjects out of these, using boot(), i would like to generate say 1000
> samples. For these 1000 samples ill calculate an nlme() and ill use
> these 1000 estimators of a variable to make further calculation. 

Whether this is valid most likely depends on what those calculations are.

> Now
> what i dont understand is where the index should be set. the nlme()
> looks like this:
> 
> nlme(Concentr~a*(1-exp(Day*(log(0.1,base=exp(1))/exp(logt09))))
>                               ,data=data
>                               ,fixed=a+logt09~1
>                               ,random=a+logt09~1|Subject[ind]
>                               ,start=list(fixed=c(a=30,logt09=1)))
> 
> My idea was to put the index ( second variable of the statistcs
> function) 

What that variable means depends on the other arguments to boot, and you 
haven't told us what those are.

> in the subject as i want to generate different samples of
> subjects. I get the error that the vector ind was not found. I would be
> happy for any help concerning this problem.



-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
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