NONMEM Users Network Archive

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Re: Bootstrap analysis

From: Nick Holford <n.holford>
Date: Tue, 21 Apr 2009 22:37:12 +0200

Varsha,

Congratulations on discovering how to use a bootstrap to evaluate the
distribution of your model parameter estimates.

The bootstrap mean is probably a more robust estimate of the true value
of the parameter than the value estimated from the original data. I
prefer to report the bootstrap mean for this reason.

The uncertainty, e.g. 95% confidence interval, can sometimes be useful
for model evaluation but more commonly is is best used to keep journal
reviewers 'happy'. There are very few other real applications of knowing
the uncertainty of a single parameter but it might be used to try to
demonstrate that a PD parameter (e.g. Emax) is different from zero and
thus indicate that the drug does something useful.

The good news is that you don't have to worry about using bootstraps "to
confirm the fact that the model I have is the best fit for the data".
The bootstrap can never confirm this for you. You need to buy a
subscription to 'Talk to God' in order to get that kind of information.

Nick


Varsha Mehta wrote:
> Group:
>
> I have bootstrap analysis (my first) parameter estimates and model
> parameters. The PDxPOP/NONMEM manual I have does not provide
> any guidance as to how I can statistically compare these two (or do I
> need to?). I also have histograms for the thetas in bootstrap analysis.
> I can make some visual judgements but is there a way to statistically
> compare the two results (bootstrap v model) built in to the NONMEM
> that I can use to quickly get some statistical comparison results?
>
> How else can I use the bootstrap results to confirm the fact that the
> model I have is the best fit for the data?
>
>
> Thanks in advance.
>
> Varsha Mehta, MS(CRDSA), Pharm.D., FCCP
> Clinical Associate Professor
> Pharmacy, Pediatrics and Communicable Diseases
> Clinical Pharmacist Neonatal Critical Care
> University of Michigan
> (O) 734-936-8985
> (F) 734-936-6946
> varsham
>
> **********************************************************
> Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues
>

--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
n.holford
mobile: +33 64 271-6369 (Apr 6-Jul 17 2009)
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Received on Tue Apr 21 2009 - 16:37:12 EDT

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