Re: OFV or Diagnostic Plot ?? Which one rules...
Sumeet,
DV vs IPRED is only one, and the least helpful plot. You may want to look on DV
vs PRED, both in original scale and on log log scale, CWRES vs time, PRED,
distributions and correlation of random effects, etc. and only then one can
decide which of the models is better. Based on the description, I would guess
that model with proportional error provides better fit at very low
concentrations, visible in log scale plots. So you may also factor this in in
the decision process. If max concentrations are more important, additive error
may help but if low concentrations are more important, you may want to use
combined or proportional error.
Regards,
Leonid
Quoted reply history
> On Feb 13, 2019, at 7:28 PM, Singla, Sumeet K <[email protected]> wrote:
>
> Hi Everyone,
>
> I am fitting two compartment PK model to Marijuana (THC) concentrations. When
> I apply proportional error (or proportional plus additive) residual model, I
> get pretty good fits (except 15% of subjects) at all time points.
> However, when I apply only additive error residual model, I get perfect fits
> in all subjects but objective functional value is increased by about 20
> units. DV vs IPRED reveal all concentrations on line of unity.
> My question is: should I go with additive error model which gives me perfect
> fit but higher OFV or should I go with proportional error model which gives
> me lower OFV but not so good fit in couple of subjects?
>
> Regards,
> Sumeet Singla
> Graduate Student
> Dpt. of Pharmaceutics & Translational Therapeutics
> College of Pharmacy- University of Iowa
>