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st: Comparing non-parametric bootstrap vs. Monte Carlo
I would like to compare the results of a 10,000-size vector non-parametric
bootstrap simuation performed on the difference of two samples of healthcare
costs drawn at patient-level with the results of a Monte Carlo simulation on
the same dataset.
My main aim would be to detect, if any, the difference between sampling with
and without reintroduction.
Is there any way with Stata 9 to perform a non-parametric Monte Carlo
simulation or should I impose a given distribution (uniform? log normal?)on
the original data set before starting the simulation?
Thanks a lot for Your Kindness and for Your Time.
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