Re: [R] Stratified Bootstrap question

From: Qian An <>
Date: Thu 31 Mar 2005 - 05:47:09 EST

Dear Tim,

Thank you very much for your information. I will try to play with S+ as you suggested. At the same time, I would like to share our idea with you about the stratified bootstrapping for my scenario. I am not sure if it is correct. I am playing with it now.

We created a new dataset containing clinic and patient id within clinic, then stratified boot() function was used to bootstrap the newly-created dataset. Based on the indices of the bootstrap result, since patient id is unique, we found the patient ids from the new dataset, then found the corresponding dataset to fit a mixed model from the original dataset using patient ids.

I am trying to run the program now, but it takes longer than what I expected. 500 times takes more than 3 hours and it is still running. I will see if this is working properly.

Thank you very much for your input,

On 30 Mar 2005, Tim Hesterberg wrote:

> 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
> (S+Resample)
> (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
> ========================================================
> | Tim Hesterberg Research Scientist |
> | Insightful Corp. |
> | (206)802-2319 1700 Westlake Ave. N, Suite 500 |
> | (206)283-8691 (fax) Seattle, WA 98109-3044, U.S.A. |
> | |
> ========================================================
> Download the S+Resample library from

Qian An
Division of Biostatistics
University of Minnesota
(phone) 612-626-2263
(fax) 612-626-8892
Email: mailing list PLEASE do read the posting guide! Received on Thu Mar 31 05:57:53 2005

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