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Questions on FOCE and log transformed data

From: Huali Wu <hualiw>
Date: Tue, 24 Feb 2009 21:04:51 -0500

Dear NMusers:

I have two questions regarding model fitting.
1. FOCE vs. FOCE with INTERACTION. I have a rich data from phase I =
study. Drug was administered by iv infusion. I used a one-compartment =
model with nonlinear clearance (Michaelis-Menten kinetics) to fit this =
data. And I tried both FOCE and FOCE with INTERACTION. The FOCE method =
generated a reasonable fit, while FOCE with INTERACTION generated a =
biased prediction (underpredict) of concentration. I thought FOCE with =
INTERACTION usually generate better result than FOCE. Does this mean my =
model is just not good enough? I used a proportional plus additional =
residual error model.
2. I also tried to fit log transformed data, but in the PRED vs. DV =
plot, the points at lower concentrations are much more scattered than =
those at higher concentrations. And this forms a trend that points are =
getting closer and closer to the line as the concentration goes up. Does =
that mean log transformation of my data is not appropriate or something =
is wrong with my residual error model? The concentration ranges from 2 =
ng/ml to 1600 ng/ml. The residual error model I used is listed as below:

$ERROR
CALLFL=0
IPRED=-3
IF(F.GT.0)IPRED=LOG(F); to avoid LOG(0)run-time error
Y=IPRED+EPS(1)


Any suggestion will be highly appreciated!

Huali
Received on Tue Feb 24 2009 - 21:04:51 EST

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