Will I obtain seriously biased results if I use bootstrapping on a subsample of a larger dataset?
Rather than drawing 100 bootstrap samples from a dataset of 50 million + records, which could hog server resources, I'm thinking of first drawing a 5% random sample, w/ replacement, of records from the master dataset. Then build bootstrapped 95% confidence intervals for several statistics of interest using the 5% sample. So in essence I'll be bootstrapping from a bootstrap sample.
I'm working with health data which is clustered according to provider and episode of care, hence drawing a proper representative 5% sample will require some care. Some earlier advice has pointed me in the right direction ( Proper bootstrapping technique for clustered data? ).