RE: Modeling concentration data with imprecise sampling time
Hi Michael,
Another method to consider would be to fit the individuals who obviously
were correctly sampled and then estimate the true infusion rate for the
other individuals iteratively.
* Subset data to IDs with correct sampling
* Fit model to those individuals
* Subset points for incorrect sampling individuals to later times (time
>> 1 hr) to estimate other parameters
* Assume 1 hr total infusion and estimate Cmax/Tmax for these
individuals (= actual end of infusion time)
* Adjust data file so that time for incorrect sampling individuals is
time + (Tmax - 1)
* Fit model with new data file.
Thanks,
Bill
Quoted reply history
-----Original Message-----
From: [email protected] [mailto:[email protected]]
On Behalf Of Leonid Gibiansky
Sent: Thursday, June 02, 2011 12:45 PM
To: [email protected]
Cc: [email protected]
Subject: Re: [NMusers] Modeling concentration data with imprecise
sampling time
Michael,
I do not think you can change observation time, but you can change
infusion duration using
RATE=-2 (in the data file)
D1=THETA(*)*EXP(ETA()) (in the control stream)
Alternative is to exclude data points that are inconsistent with the
profiles.
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
On 6/2/2011 11:44 AM, [email protected] wrote:
>
> All:
> I have a data set following a constant rate 1-hour infusion where the
> time of 1-hour sample is imprecise. In some cases the "1-hr" sample
was
> taken prior to infusion termination as it was intended; however, in
> others it was quite apparently take after the infusion ended. I'm
> thinking of modeling with the time of the "1-hr" sample as a "theta".
> Does anyone have a NONMEM coding example showing how to do this? Any
> other suggestions as to how to handle this would be appreciated as
well.
>
> Thanks,
> Michael