for(imputation.number in 1:number.of.multiple.imputations) {
Compute residuals from n observations, off of predictions for the
target variable
Sample with replacement n of these n residuals
Sample with replacement m of these n sampled with replacement
Add these m random residuals to the predicted expected values of
the target variable
fit the model on the completed dataset for this imputation.number
}
If we weren't doing multiple imputation,
sample(sample(res,n,rep=T), m, rep=T)
would do the trick. But I want to quickly form an m x number.of
multiple.imputations matrix of residuals without a for loop.
I'll post a summary of solutions that are E-mailed to me.
Thanks -Frank Harrell
-----------------------------------------------------------------------
This message was distributed by s-news@wubios.wustl.edu. To unsubscribe
send e-mail to s-news-request@wubios.wustl.edu with the BODY of the
message: unsubscribe s-news