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PRIOR method without covariance matrix of estimates?

From: Kaessner, Nele <nele.kaessner>
Date: Thu, 13 Oct 2011 07:31:03 +0200

Dear all,

I am currently in a planning phase for a PopPK evaluation for an upcoming s=
tudy. I have already developed a PopPK model for this compound, and the ide=
a would now be to fit the available model to the new data. One idea was to =
do this via the PRIOR functionality in NONMEM, so that I do not have to mix=
 the old data into the new data set. So now I wanted to test the performanc=
e of this approach via simulations, and have the following problem:
My previously developed final model did not converge successfully (terminat=
ed with rounding errors), so I do not have a covariance matrix of estimates=
 to describe the uncertainty in the THETAs. However I obtained confidence i=
ntervals from a nonparametric bootstrap, and I was wondering if these resul=
ts can somehow be used instead for the prior information.
In some internal discussions we had the idea to just use all the parameter =
estimates from the performed 1000 bootstrap runs, and just calculate varian=
ce and covariance of THETAs from these.
I would highly appreciate your comments on the validity of such an approach=
, or suggestions of other alternatives.

Thanks and best regards

Dr. Nele Kner
PK/PD Sciences
Modelling and Simulation (RDP/MS)

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mailto: nele.kaessner<>

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Received on Thu Oct 13 2011 - 01:31:03 EDT

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