Re: RE: VPC, NPC or PPC?

From: Saik Urien Svp Date: February 26, 2009 technical Source: mail-archive.com
Hello Regarding the NPDE metrics, at the last PAGE we had a discussion with France Mentré, Emmanuelle Comets and Karl Brendel and agreed that it should be juged on - the visual aspect (distribution of npde) -the mean is not significantly different from 0 -and the variance is not significantly different from 1 However, I experienced a non negligible number of model fittings for which the normality test was OK Perhaps France will further comment on this Saïk Dr Saik URIEN Directeur de Recherche à l' INSERM C.I.C. Mère-enfant Cochin-Necker E.A.3620 - Université Paris Descartes Unité de Recherche Clinique (URC) HOPITAL TARNIER 89 rue d'Assas F75006 PARIS 01 5841 2880 Email : [email protected]
Quoted reply history
----- Original Message ----- From: "Stephen Duffull" <[email protected]> To: "SIMON Nicolas" <[email protected]>; <[email protected]> Sent: Wednesday, February 25, 2009 7:33 PM Subject: [NMusers] RE: VPC, NPC or PPC? > Nicolas > > > We have a dataset with as many dosing (amount and length of > > infusion) as patients. Once the final model was defined, I > > have performed a vpc. However, because the dosing are very > > different between patients, is it relevant to perform vpc or > > shall we compute npc or ppc? > > > > > > > > Can somebody explain the basic difference between vpc, npc > > and ppc and when shall we used one or the other? > > > > Despite how it sounds this is not really a simple question. > > Mostly the purpose of all of these techniques is to assess how well the model describes the data. This can be achieved visually and numerically. If you want your method to have "diagnostic" properties, i.e. an ability to determine where the model may fail, then visual types of checks tend to be more informative. Numerical types of checks really give you an overall feeling of whether your model fits the data but don't often allow you to determine where in particular the model might fail. > > Numerical checks include PPC and NPDE (and others). PPC is really a Bayesian construct as it checks the posterior distributions of your parameters and hence isn't naturally something that would be performed in an MLE framework. However there have been many examples where PPCs have been performed in NONMEM (publications on this have appeared in JPKPD). PPC is generally used to test a specific (important) feature of the data (hence is generally not diagnostic for the whole model). NPDE provides a more general numerical description of agreement of model and data, but when the statistic is tested it seems to reject most model (hence is not diagnostic). > > Despite the apparent division into visual and numerical there is no reason why a "VPC" couldn't be expressed numerically as a numerical predictive check and why PPC or NPDE style techniques could not be expressed graphically. We have recently produced examples of visual versions of PPC as a form of visual predictive check for situations similar to what you have described where traditional VPCs don't work well (note we did this in WinBUGS). > > Steve > -- > Professor Stephen Duffull > Chair of Clinical Pharmacy > School of Pharmacy > University of Otago > PO Box 913 Dunedin > New Zealand > E: [email protected] > P: +64 3 479 5044 > F: +64 3 479 7034 > > Design software: www.winpopt.com > > >
Feb 25, 2009 Simon Nicolas VPC, NPC or PPC?
Feb 25, 2009 Stephen Duffull RE: VPC, NPC or PPC?
Feb 25, 2009 Leonid Gibiansky Re: VPC, NPC or PPC?
Feb 26, 2009 Saik Urien Svp Re: RE: VPC, NPC or PPC?
Feb 26, 2009 Leonid Gibiansky Re: VPC, NPC or PPC?