Re: FW: Parameter uncertainty
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:*[email protected]
> [mailto:[email protected]] *On Behalf Of *Fanny Gallais
> *Sent:* Wednesday, February 15, 2017 5:55 AM
> *To:* [email protected]
> *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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