Re: FW: [NMusers] Parameter uncertainty

From: Leonid Gibiansky <lgibiansky_at_quantpharm.com>
Date: Wed, 15 Feb 2017 09:31:04 -0500

One of the tools available for simulations is Metrum R package

metrumrg

install.packages("metrumrg", repos="http://R-Forge.R-project.org")

Example of applications can be found here:

http://www.page-meeting.org/page/page2006/P2006III_11.pdf

Since the time it was written (2005-2006), Nonmem enhanced the
simulations options, so now you can simulate from the model-estimated
uncertainty directly from Nonmem. The R package could be useful if you
do it from the bootstrap results.

Leonid

>
> *From:*owner-nmusers_at_globomaxnm.com
> [mailto:owner-nmusers_at_globomaxnm.com] *On Behalf Of *Fanny Gallais
> *Sent:* Wednesday, February 15, 2017 5:55 AM
> *To:* nmusers_at_globomaxnm.com
> *Subject:* [NMusers] Parameter uncertainty
>
> Dear NM users,
>
>
>
> I would like to perform a simulation (on R) incorporating parameter
> uncertainty. For now I'm working on a simple PK model. Parameters were
> estimated with NONMEM. I'm trying to figure out what is the best way to
> assess parameter uncertainty. I've read about using the standard errors
> reported by NONMEM and assume a normal distribution. The main problem is
> this can lead to negative values. Another approach would be a more
> computational non-parametric method like bootstrap. Do you know other
> methods to assess parameter uncertainty?
>
>
>
>
>
> Best regards
>
>
>
> F. Gallais
>
>
>
>
>
>
>
>
>
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Received on Wed Feb 15 2017 - 09:31:04 EST

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