From your description, it sounds like you want to just run a calculation
for each of the 20 data sets. This could be done using miApply() or
miEval() in the missing data library (use library(missing)).
I would recommend that you not use the bootstrap() function to do the 20
calculations, because that could lead to confusion. From my understanding
of your intent, it actually has nothing to do with bootstrapping.
This would capture only one of two source of variation (would capture
variation due to multiple imputations, would not capture variation due
to the original sample being randomly sampled from a population,
which is what bootstrapping is for), and hence would lead to
confidence intervals that are much too short if you use bootstrap
confidence interval routines.
There are routines in the missing data library that incorporate
both sources of variation, provided that the results of each imputation
include standard errors that reflect the sampling variability.
Tim Hesterberg
>Dear S folks,
>
>I occasionally use S plus with the menu and wonder if anyone's willing to
>share a few lines of code to solve the following task, which is essentially
>data management.
>
>I have twenty imputed datasets because my original data had 20% missing
>data which looks to be MAR using the ISNI index of Troxell et al. I want to
>bootstrap the coefficients of a model that will be fit to each of the
>twenty imputed datasets. The logical approach seems to be to bootstrap each
>of the 20 datasets and then combine all the output and take the grand mean
>and grand percentiles to construct the final bootstrap estimate and
>confidence intervals.
>
>The bootstrap command from the point and click menu works like this:
>
>coef(lm(response~predictor, data.frame))
>
>What I want to to do is run the bootstrap function for twenty different
>data sets that are combined in one data file, and indexed with a variable
>called _imputation_ = 1,2, ..., 20.
>
>Any ideas in how I might code this in S plus?
>
>Thanks in advance for your help.
>
>Terrence E. Murphy, Ph.D.
>Program on Aging
>Yale University
>1 Church St., 7th Floor
>New Haven, CT 06437
>terrence.murphy@yale.edu
>phone: 203-764-9805
>fax: 203-764-9831
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