RE: [NMusers] Parameter uncertainty

From: Eleveld-Ufkes, DJ <d.j.eleveld_at_umcg.nl>
Date: Wed, 15 Feb 2017 11:10:05 +0000

Hi Fanny,
Likelihood profiles are very useful to asses parameter uncertainty.
I am sure you find a tutorial somewhere how they work.
A number of software packages automate the process quite a bit.
They are usually much more computationally efficient than bootstrap.
Warm regards,
Douglas Eleveld

From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com] On Behalf Of Fanny Gallais
Sent: woensdag 15 februari 2017 11:55
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 - 06:10:05 EST

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