NONMEM Users Network Archive

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RE: OMEGA selection

From: Bachman, William <William.Bachman>
Date: Wed, 15 Apr 2009 12:12:56 -0400

Well, the first thing that I would do is look at the magnitude of the
estimates of the etas. I would eliminate those etas that are poorly
estimated (essentially the very large values or those approaching zero).

________________________________

From: owner-nmusers
On Behalf Of Ethan Wu
Sent: Wednesday, April 15, 2009 11:47 AM
To: nmusers
Subject: [NMusers] OMEGA selection



Dear all,

  I am fitting a PD response, and the equation goes like this:

total response = baseline+f(placebo response) +f(drug response)

first, I tried full omega block, and model was able to converge, but
$COV stop failed.

To me, this indicates that too many parameters in the model. The
structure model is rather simple one, so I think probably too many Etas.


I wonder is there a good principle of Eta reduction that I could
implement here. Any good reference?



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Received on Wed Apr 15 2009 - 12:12:56 EDT

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