RE: Parameter uncertainty
Hi Fanny,
As I understand it, you’re looking for ways to produce predictions according to
your model taking into account parameter uncertainty.
We’ve recently published on the importance of parameter uncertainty when
considering probability of target attainment for antibiotic dosing regimens.
(Colin et al. J Antimicrob Chemother (2016) 71 (9): 2502-2508)
The online supplement to this paper holds an R-script which you can use to
simulate (and calculate PTA, if relevant) taking into account parameter
uncertainty. For this, the script uses the variance-covariance matrix that is
produced by the $COV step in NONMEM. Of course other techniques which generate
a var-cov matrix could be used as input for the script as well.
Kind regards,
Pieter Colin
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Fanny Gallais
Sent: woensdag 15 februari 2017 11:55
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