Re: PRIOR method without covariance matrix of estimates?
Nele,
Nonmem 7.2 has UNCONDITIONAL option in cov step that would compute SEs even for problems with error in minimization.
Also, it is perfectly OK to have variance-covariance computed from bootstrap; some may even argue that it is better than use Nonmem cov matrix.
And finally (just an opinion) I would rather combine the data than use priors.
Thanks
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
Quoted reply history
On 10/13/2011 1:31 AM, Kaessner, Nele wrote:
> Dear all,
>
> I am currently in a planning phase for a PopPK evaluation for an
> upcoming study. I have already developed a PopPK model for this
> compound, and the idea 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 performance of this approach via simulations, and
> have the following problem:
>
> My previously developed final model did not converge successfully
> (terminated with rounding errors), so I do not have a covariance matrix
> of estimates to describe the uncertainty in the THETAs. However I
> obtained confidence intervals from a nonparametric bootstrap, and I was
> wondering if these results 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 variance 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
>
> Nele
>
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> Dr. Nele Käßner
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