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From: Leonid Gibiansky <LGibiansky>
Date: Fri, 25 Jul 2008 19:14:49 -0400

I cannot make any general statements but here is the summary of the 13
different models that I tested for comparison of bootstrap and nonmem CI.

Note that all bootstrap samples were appropriately stratified by major
covariates (such as study, dose, weight as necessary, etc.).


Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
e-mail: LGibiansky at
tel: (301) 767 5566

> Dear Dr. Holford,
> Please correct me if I am wrong, however my understanding is that
> asymptotic distribution implied by NONMEM's covariance step approaches
> normality as the sample size gets larger or we have more data. However,
> a non parametric bootstrap distribution may have poor coverage with a
> small sample size as well, since it relies on sampling subjects with
> repalcement in the data set. So both distributions have problems when
> sample size is small (e.g. N<30). Therefore I would think when N is
> large the wald based Confidence Intervals from NONMEM are appropriate
> enough. It would be helpful to know the criteria when generating a non
> parametric bootstrap distribution is really advantageous.
> Thanks, Mohamed
> Quoting Nick Holford <n.holford
Received on Fri Jul 25 2008 - 19:14:49 EDT

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