Re: residual variability
What I meant was that after you remove the random effect on the lag time (and stabilize the model) you may introduce inter-individual variability on delay by using transit compartment with random effect or zero-order absorption with random effect on duration of infusion (followed by the first-order).
Leonid
Quoted reply history
On 9/29/2016 12:53 AM, Sultan,Abdullah S wrote:
> Hi Dr. Gibiansky
>
> Thanks, removing the random effect on the lag time help stabilize the model.
>
> I used a transit compartment and sequential and it did not help, I still
> get very large parameter estimates.
>
> I am using Monolix for the modeling
>
> Thanks,
>
> Abdullah
>
> ------------------------------------------------------------------------
> *From:* Leonid Gibiansky <[email protected]>
> *Sent:* Tuesday, September 27, 2016 5:49:00 PM
> *To:* Sultan,Abdullah S; [email protected]
> *Subject:* Re: [NMusers] residual variability
>
> Abdullah,
> Do you have random effect on the lag time? Models with random effects on
> the lag time are very difficult to work with, try to remove the lag and
> use the transit compartment(s) to describe the delay. Make sure you have
> INTERACTION option on the estimation step, use METHOD=1. Sometimes
> models with sequential 0-order and 1-st order absorption describe delay
> better (with estimated D1 of infusion to the depot compartment).
> Leonid
>
> On 9/27/2016 1:12 PM, Sultan,Abdullah S wrote:
>
> > Hi everyone,
> >
> > I have a rich data set for a drug administered orally. The drug has slow
> > absorption (Tmax 4 hours) and rapid elimination (2 hours half life). A
> > tlag model was sufficient to describe the data but I ran
> > into difficulties with the error model.
> >
> > If I use a proportional or combined error model, the model is unstable
> > and I get unrealistic estimates (very large Vd, Cl and residual
> > variability) . It is only stable if:
> >
> > 1) I use a constant error model
> >
> > 2) Use a combined error model and fix the a part
> >
> > When I use a constant error model, the diagnostic plots clearly show the
> > error is not constant
> >
> > Not sure what the cause for this is, I tried several things to fix it
> > like changing initial estimates or structural model (transit
> > compartment, zero order,....), deleting outliers or low concentrations
> > near the BLQ but the problem still persists.
> >
> > Any suggestions
> >
> > Thanks,
> >
> > Abdullah Sultan