-----Original Message-----
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Nick Holford
Sent: Friday, July 01, 2011 11:11 AM
To: nmusers
Subject: Re: [NMusers] CCV or Additive error models?
Yuanyue,
It is has been well established and discussed at length on nmusers that a
successful $COV step says nothing about the suitability of the model to
describe the data.
On the other hand the OFV is a very reliable statistic for model selection.
You should use the combined error model.
Nick
On 1/07/2011 5:17 p.m., [email protected] wrote:
> Dear nmusers,
>
> In one of my PK analysis, if I chose Y=F+F*ERR(1)+ERR(2), I got lower
> objective value=1130.907, but $COV step failed (S matrix is singular);
> when I chose Y=F+ERR(1), I got $COV successful but higher objective
> value=1351.735. I prefer to choose the addivtive error model even if
> with higher objective value because it seems comfortable to see $COV
> successful. Can anyone give me other suggestions?
>
> Thanks
>
>
> Yuanyue (Paul) Gao
>
> School of Pharmacy
> University of Pittsburgh
> 716 Salk Hall
> 3501 Terrace Street
> Pittsburgh, PA 15261
> Phone: 412-648-8546
> E-mail: [email protected]
>
--
Nick Holford, Professor Clinical Pharmacology Dept Pharmacology& Clinical
Pharmacology University of Auckland,85 Park Rd,Private Bag
92019,Auckland,New Zealand tel:+64(9)923-6730 fax:+64(9)373-7090
mobile:+64(21)46 23 53
email: [email protected]
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
-----------------------------------------------------
Confidentiality Notice: This e-mail transmission
may contain confidential or legally privileged
information that is intended only for the individual
or entity named in the e-mail address. If you are not
the intended recipient, you are hereby notified that
any disclosure, copying, distribution, or reliance
upon the contents of this e-mail is strictly prohibited.
If you have received this e-mail transmission in error,
please reply to the sender, so that we can arrange
for proper delivery, and then please delete the message
from your inbox. Thank you.