RE: Parameterization!!!
From: "Bachman, William" <bachmanw@globomax.com>
Subject: RE: Parameterization!!!
Date: Wed, 9 May 2001 16:25:30 -0400
Sometimes one parameterization can be more stable for a given set of data than another parameterization. It may be related to how the random errors enter into the model rather than the fixed effect parameters. You could try reparameterizing within TRANS1 to get the more important parameters like CL. (You already have KA AND V2). It's less likely the peripheral parameters will be important in your model. They are typically poorly defined. Also, once you begin to explain more of the variability in your data through addition of covariates, it may be possible to go back and try the TRANS4 parameterization (this time incorporating the covariates you've discovered) and obtain a successful minimization comparable to the TRANS1 fit.
$SUB ADVAN4 TRANS1
$PK ;reparam for CL
CL =THETA(1)*EXP(ETA(1))
KA =THETA(2)*EXP(ETA(2))
K23=THETA(3)*EXP(ETA(3))
K32=THETA(4)*EXP(ETA(4))
V2 =THETA(5)*EXP(ETA(5))
K=CL/V2
S2=V2
William J. Bachman, Ph.D.
GloboMax LLC
7250 Parkway Dr., Suite 430
Hanover, MD 21076
Voice (410) 782-2212
FAX (410) 712-0737
bachmanw@globomax.com
Quoted reply history
-----Original Message-----
From: Sreenivasa Rao Vanapalli [mailto:svanapal@blue.weeg.uiowa.edu]
Sent: Wednesday, May 09, 2001 3:51 PM
To: Bachman, William
Subject: RE: Parameterization!!!
Yes I did try as you said. But the result is same. I'm really wondering what is going on behind the screen. TRANS1 fit gives better estimates. With TRANS4 I tried fixing the VD value. But V3 esimate became astronomical so was KA. And corresponding predicted values (more than 100 times the observed values!!!). I'm really not sure what to do. I need to do some covariate effect studies once the this model issue is settled.
Sreenivasa Vanapalli
-----Original Message-----
From: Bachman, William [mailto:bachmanw@globomax.com]
Sent: Wednesday, May 09, 2001 2:47 PM
To: 'Sreenivasa Rao Vanapalli'
Subject: RE: Parameterization!!!
How did the objective function values and the goodness of fit plots compare between TRANS1 and TRANS4? Are you sure you have a global minimum in both fits? (try different initial estimates to verify). If TRANS1 fit is better, try calculating new initial estimates for TRANS4 based on the TRANS1 final estimates and the relationships between the two parameterizations. Also be aware of potential for flip-flop with your model.
William J. Bachman, Ph.D.
GloboMax LLC
7250 Parkway Dr., Suite 430
Hanover, MD 21076
Voice (410) 782-2212
FAX (410) 712-0737
bachmanw@globomax.com