Hello NMUSERS,
Let me just add one more thought on the bootstrap discussion. Sometimes when
doing a bootstrap it happens that the runs terminate because of parameter
estimates near to the boundary (e.g. values for OMEGA close to 0). When this
happens in a considerable number of runs, lets say
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of andreas lindauer
Sent: Thursday, July 31, 2008 7:27 AM
To: nmusers@globomaxnm.com
Subject: RE: [NMusers] PPC
Hello NMUSERS,
Let me just add one more thought on the bootstrap discussion. Sometimes
Andreas,
If this happens to 10% of your runs then its pretty strong evidence that
the uncertainty in the OMEGA estimate would lead to a 95% CI very close
to zero. I would consider simplifying the model and fixing that OMEGA to
0. Then evaluate the model for its intended purpose and decide if
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Nick Holford
Sent: Friday, July 25, 2008 5:14 PM
To: nmusers
Subject: Re: FW: [NMusers] PPC
Matt,
Thanks for your comments which I almost completely agree with.
You propose to log transform the parameters so
: [NMusers] PPC
Matt,
Thanks for your comments which I almost completely agree with.
You propose to log transform the parameters so that the resulting
unlogged uncertainty will be skewed. But if this does not mean you will
get a better picture of the uncertainty. If the 'true' parameter
To: Nick Holford; nmusers@globomaxnm.com
Subject: RE: FW: [NMusers] PPC
Hi Nick,
I have been following this discussion and I think it is very helpful to
many of us. Can you please elaborate on that last part about binning?
What is that for? I must have missed something there.
Thanks,
Susan
PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Nick Holford
Sent: Friday, July 25, 2008 2:12 AM
To: nmusers@globomaxnm.com
Subject: Re: FW: [NMusers] PPC
Mahesh,
Thanks for your further info on VPC and PPC. I agree that the bootstrap
distribution of the parameters is probably better than
VPC
be enough for model verification?
Kindly advise...Mahesh
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] Behalf Of Willavize, Susan A
Sent: Wednesday, July 23, 2008 8:38 AM
To: Nick Holford; nmusers@globomaxnm.com
Subject: RE: FW: [NMusers] PPC
Hi Nick,
I
Mohamed,
When the number of subjects is small then any confidence interval is
going to be wide and probably no-one is really interested in it. With
studies more suitable for population analysis (at least 25 subjects and
preferably over 100 if you want to look for covariate effects) then the
Matthew Westwood wrote:
From: Paul Matthew Westwood
Sent: 22 July 2008 13:20
To: Nick Holford
Subject: RE: [NMusers] PPC
Nick,
Thanks for your reply and apologies once again for another confusing email. I
think I am using VPC, which as I understand
-mail is classified as Pfizer Confidential; it is confidential and
privileged.
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Nick Holford
Sent: Wednesday, July 23, 2008 6:32 AM
To: nmusers@globomaxnm.com
Subject: Re: FW: [NMusers] PPC
Paul
PROTECTED] Behalf Of Willavize, Susan A
Sent: Wednesday, July 23, 2008 8:38 AM
To: Nick Holford; nmusers@globomaxnm.com
Subject: RE: FW: [NMusers] PPC
Hi Nick,
I have been following this discussion and I think it is very helpful to
many of us. Can you please elaborate on that last part about binning
Hello all,
I wonder if someone can give me some tips on PPC.
I am working on a midazolam dataset with a pediatric population, and have
decided to use PPC as a model validation technique. The dataset I am modelling
has up to 43 patients, at different ages, different weights, different times of
Paul,
Its not clear to me if you did a VPC (visual predictive check) using
just the final estimates of the parameters) or tried to do a posterior
predictive check (PPC) including uncertainty on the parameter estimates
in the simulation.
I dont have any experience with PPC but I dont think
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