Re: residual variability
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
Quoted reply history
________________________________
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
>