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 <lgibian...@quantpharm.com> Sent: Tuesday, September 27, 2016 5:49:00 PM To: Sultan,Abdullah S; nmusers@globomaxnm.com 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 >
