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Comaprison of two models

From: Robert Kalicki <robert.kalicki>
Date: Sat, 26 Jun 2010 11:51:11 +0200

Dear NMusers

 

I would like to compare two models. Let’s say the model M1 and the =
model M2.

The model M1 is a simple one with just one observation compartment (Y =
=
IPRE*(1+ERR)). The second one is a more complex one with three =
observation
compartments (Y1 = IPRE1*(1+ERR1); Y2=IPRE2*(1+ERR2); =
Y3=IPRE3*(1+ERR3)).

The data sets are identical with regards to the first observation
compartment. Y form M1 is in fact Y1 from M2 and Y2 and Y3 from M2 are
additional observations which should improve the model because of =
additional
information or perhaps not because of additional noise.

If I am interested in comparing the two models focusing on the first
observation (i.e. Y form M1 and Y1 form M2, respectively), I cannot use =
the
OFV, since OFV2 (OFV for M2) will be a global measure of the fit =
including
Y2 and Y3 from M2.

So, how can I perform an estimation of M2 including the three =
observations
and then isolate the contribution of Y1 to the global OFV2?

May I assume additional properties of OFV, i.e. OFTtotal = =
OFV1+OFV2+OFV3?

Is it possible to code the model so that only OFV1 will be computed?

 

Many thanks in advance. Let me know if you need additional information.

 

Best regards

 

Robert

 

 

___________________________________________
Robert M. Kalicki, MD

Postdoctoral Fellow

Department of Nephrology and Hypertension

Inselspital

University of Bern

Switzerland

 

Address:

Klinik und Poliklinik für Nephrologie und Hypertonie

KiKl G6

Freiburgstrasse 15

CH-3010 Inselspital Bern

 

Tel +41(0)31 632 96 63

Fax +41(0)31 632 14 58

 


Received on Sat Jun 26 2010 - 05:51:11 EDT

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