Hi Patricia,
What is the purpose of your modeling exercise? I am not sure your scenario
could be assigned to any particular distribution. If you intend to simulate
population from the model, then your assumptions would not be reasonable. If
you have rich data, you may try individual modeling ap
Hi Patricia,
What is the purpose of your modeling exercise? I am not sure your scenario
could be assigned to any particular distribution. If you intend to simulate
population from the model, then your assumptions would not be reasonable. If
you have rich data, you may try individual modeling ap
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 inco
Just realized the typical value of this estimate cannot be 1.0. You may need
other transformation.
Sam
> On August 5, 2020 9:59 AM Sam Liao wrote:
>
>
> Dear Patricia,
> This distribution might to analogous to relative bioavailability estimate,
> which is bounded between 0 to 1. Typically,
Dear Patricia,
This distribution might to analogous to relative bioavailability estimate,
which is bounded between 0 to 1. Typically, we use the logit-transformation in
F1 estimate.
For example:
m1 = log(θ1/(1- θ1))
EE1 = m1 + η1
F1 = exp(EE1)/[1 +exp(EE1)]
Best regard
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
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 thi
