NONMEM Users Network Archive

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RE: Linear VS LTBS

From: Mats Karlsson <mats.karlsson>
Date: Mon, 24 Aug 2009 04:01:55 +0200

Hi Steve,

I think you're missing an important point. As I wrote to Nick, you will
never get concentrations reported regardless of their value. At some point,
you will only get the information that concentration is below a limit
(LOQ,LOD,LO?). This you should take into account in your design. Error
models for concentrations below LO? are not entirely unimportant, but will
not have the properties you mention below.

Best regards,

Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003

-----Original Message-----
From: Stephen Duffull [mailto:stephen.duffull
Sent: Monday, August 24, 2009 2:49 AM
To: Mats Karlsson; 'Nick Holford'; 'Leonid Gibiansky'
Cc: 'nmusers'
Subject: RE: [NMusers] Linear VS LTBS


Just a comment on your comments below:

"All models are wrong and I see no reason why the exponential error model
would be different although I think it is better than the proportional error
for most situations. "

"Why would you not be able to get sensible information from models that
don't have an additive error component?"

I agree that for estimation purposes a purely proportional or exponential
error model often seems to work well and under the principles of "all models
are wrong" it may well be appropriately justified. This is probably because
estimation processes that we use in standard software are fairly robust to
trivial solutions. The theory of optimal design is less forgiving in this
light and if you stated that your error was proportional to the observation
then it would conclude that there would be no error when there is no
observation (which we know is not true due to LOD issues). All designs are
optimal when there is zero error since the information matrix would be
infinite. Practically, the smallest observation will have least error and
hence be in some sense close to optimal.

So, a proportional or exponential only error model should be used with
caution in anything other than estimation and not used for the purposes of
optimal design.


Received on Sun Aug 23 2009 - 22:01:55 EDT

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