Similar to Leonid's solution, you can try using an exponential distribution:
D1 = DUR*(1-EXP(-EXP(ETA(1)))) The exponential within an exponential gives left skew and ensures that D1 ≤ DUR. For subjects who you know had an incomplete infusion duration, I would add an indicator variable (1 if incomplete, 0 if full duration) so that the subjects with complete duration have the known complete duration. D1 = DUR*(1 - Incomplete*EXP(-EXP(ETA(1)))) Thanks, Bill -----Original Message----- From: owner-nmus...@globomaxnm.com <owner-nmus...@globomaxnm.com> On Behalf Of Leonid Gibiansky Sent: Wednesday, August 5, 2020 12:51 PM To: Patricia Kleiner <pkle...@uni-bonn.de>; nmusers@globomaxnm.com Subject: Re: [NMusers] Variability on infusion duration may be D1=DUR*EXP(ETA(1)) IF(D1.GT.DocumentedInfusionDuration) D1=DocumentedInfusionDuration On 8/5/2020 12:18 PM, Patricia Kleiner wrote: > Dear all, > > I am developing a PK model for a drug administered as a long-term > infusion of 48 hours using an elastomeric pump. End of infusion was > documented, but sometimes the elastomeric pump was already empty at > this time. Therefore variability of the concentration measurements > observed at this time is quite high. > To address this issue, I try to include variability on infusion > duration assigning the RATE data item in my dataset to -2 and model > duration in the PK routine. Since the "true" infusion duration can > only be shorter than the documented one, implementing IIV with a > log-normal distribution > (D1=DUR*EXP(ETA(1)) cannot describe the situation. > > I tried the following expression, where DUR ist the documented > infusion > duration: > > D1=DUR-THETA(1)*EXP(ETA(1)) > > It works but does not really describe the situation either, since I > expect the deviations from my infusion duration to be left skewed. I > was wondering if there are any other possibilities to incorporate > variability in a more suitable way? All suggestions will be highly > appreciated! > > > Thank you very much in advance! > Patricia > > >
