RE: [NMusers] PRED for BLQ-like observations

From: Pavel Belo <nonmem_at_optonline.net>
Date: Fri, 20 Nov 2015 17:15:35 -0500 (EST)

That is perfect!
 P.
 
 
On Fri, Nov 20, 2015 at 04:04 PM, Bauer, Robert wrote:
 
 




Unfortunately adding records to estimation slows down estimation even
with MDV=1 records. Please do a search on MDV=101 option in nm730.pdf
1 (section Ignoring Non-Impact Records During Estimation (NM73)).  The=
se
records will be used only on the $TABLE step.

 

 



Robert J. Bauer, Ph.D.

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ICON Early Phase

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From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com]
On Behalf Of Nick Holford

Sent: Friday, November 20, 2015 12:39 PM

To: nmusers

Subject: Re: [NMusers] PRED for BLQ-like observations





 

Pavel,

Did you test the run time with double the records?

I would expect that the MDV=1 records would be largely ignored in the

estimation step and not contribute much to run time.

Nick



On 21-Nov-15 08:59, Pavel Belo wrote:

> Thank you Bill,

> In my case it exactly doubles the number of records... The records

> are daily measures and the code is running slow enough. I'll split the

> code into estimation part and one that that is redundant, but uses a

> larger file and creates an output. It will be something like

> $EST MAXEVALS=9999 SIG=3 NOABORT PRINT=1 SORT CONSTRAIN=5

> METHOD=SAEM NBURN=0 NITER=0 POSTHOC INTERACTION

> LAPLACIAN GRD=TG(1-7):TS(8-9) CTYPE=3 CINTERVAL=10

> I guess the best future way is modify something in NONMEM so there is

> an option to provide only PRED in the PRED column (version 7.4?).

> Thanks!

> Pavel

> On Fri, Nov 20, 2015 at 01:06 PM, Denney, William S. wrote:

>

> Hi Pavel,

>

> The easiest way that I know is to generate your data file with one

> set of rows for estimation with M3 and another row just above or

> below with MDV=1. NONMEM will then provide PRED and IPRED in the

> rows with MDV=1.

>

> Thanks,

>

> Bill

>

> *From:*owner-nmusers_at_globomaxnm.com

> [mailto:owner-nmusers_at_globomaxnm.com
> <mailto:owner-nmusers_at_globomaxnm.com> ] *On Behalf Of *Pavel Belo

> *Sent:* Friday, November 20, 2015 11:47 AM

> *To:* nmusers_at_globomaxnm.com <mailto:nmusers_at_globomaxnm.com>

> *Subject:* [NMusers] PRED for BLQ-like observations

>

> Hello The NONMEM Users,

>

> When we use M3-like approach, the outputs has PRED for non-missing

> observations and something else for BLQ (is that PRED=CUMD?). As

> in the diagnostic figures PRED for BLQs looks like noise, I remove

> them. It is not always perfect, but OK in for most frequent cases.

>

> When we use count data such as a scale with few possible values

> (for example, 0, 1, 2, 3, 4, 5), it makes more sense to use PHI

> function (home-made likelihood) for all observations rather than

> to treat the count as a continuous variable an apply M3-like

> approach to 1 and 5 while only (as we know, they are like LLOQ and

> ULOQ). In this case, all PRED values look like noise. A hard way

> to replace the noise with PRED value is to simulate PRED for each

> point and merge them with the DV and IPRED data. Is there an easy

> way?

>

> (The model runs well and better than when the count is treated as

> a continuous variable.)

>

> Thanks!

>

> Pavel

>



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Nick Holford, Professor Clinical Pharmacology

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University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand

office:+64(9)923-6730 mobile:NZ+64(21)46 23 53

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<http://holford.fmhs.auckland.ac.nz/>



Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A,
Pypendop, B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite
pharmacokinetic models - tests of assumptions and predictions. Journal
of Pharmacology & Clinical Toxicology. 2014;2(2):1023-34.

Holford N. Clinical pharmacology = disease progression + drug action. Br=
 
J Clin Pharmacol. 2015;79(1):18-27.








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Received on Fri Nov 20 2015 - 17:15:35 EST

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