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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 =
compartments (Y1 = IPRE1*(1+ERR1); Y2=IPRE2*(1+ERR2); =

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 =
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 =
OFV, since OFV2 (OFV for M2) will be a global measure of the fit =
Y2 and Y3 from M2.

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

May I assume additional properties of OFV, i.e. OFTtotal = =

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 M. Kalicki, MD

Postdoctoral Fellow

Department of Nephrology and Hypertension


University of Bern




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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