Stratified Bootstrap question

Dear Qian,

You might try the S+Resample library, which has built-in support
for both sampling by subject and stratified sampling.

If you are a student, there is a free student version of S+.

See
www.insightful.com/downloads/libraries	(S+Resample)
www.insightful.com/Hesterberg/bootstrap	(has link to the student version)

For the missing values, consider the S+Missing library,
which offers multiple imputation.  With S+, do
	library(missing)

Tim Hesterberg

P.S.  The combination of sampling by subject and stratified sampling
was terribly messy to program.  If I'd known in advance how messy, I
never would have done it :-(  But it is done now.

Dear R users,

I have a question regarding stratified bootstrap question and how to implement
it using boot() in R's boot package.

My dataset is a longitudinal dataset (3 measurements per person at year
1, 4 and 7) composed of multiple clinic centers and multiple participants
within each clinic. It has missing values.

I want to do a bootstrap to find the standard errors and confidence
intervals for my variance components. My model is a mixed model with
random clinic and random participant within clinic.

I thought two methods to do bootstrap:
(1) bootstrap data; however, I have problem specifying the second
parameter for my statistic function, shall I use indices, weight or
frequency and how shall I relate to my dataset.
(2) bootstrap residuals; however, the dataset has multiple measurements
and missing values. I am wondering how to construct a new data frame
containing the residuals and fitted values.

Any ideas will be highly appreciated!
Sincerely yours,
Qian

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| Tim Hesterberg       Research Scientist              |
| timh at insightful.com  Insightful Corp.                |
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Download the S+Resample library from www.insightful.com/downloads/libraries