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RE: estimating Ka from dataset combining rich sample study and sparse sampling study

From: Ribbing, Jakob <Jakob.Ribbing>
Date: Wed, 17 Jun 2009 21:43:28 +0100

Hi Ethan,


If OMEGA(?) for KA is drastically reduced when including the sparse
data, then something is wrong with your model and in this case it is not
the estimation method or assumption on distribution of individual
parameter). Eta-shrinkage would not drastically reduce the estimate of
OMEGA, since this estimate is driven by the subjects/studies which
contain information on the parameter.


If the sparse data is multiple dosing it may be that KA is variable
between occasions, rather than between subjects (assuming the sparse
data contain some information on KA). Or if the sparse data is from a
less well-controlled study or a different population, it may be that
increased IIV in other parts of the model (e.g. OMEGA on V) is making
IIV in KA appear low for the rich study, when fitting the two studies
together. If you get the covariate model in place this problem will be
solved. For the simple model you have it should be quick to start out
assuming that most parameters (THETAs and OMEGAs) are different between
the two studies and then reduce down to a model which is stable and
parsimonious. Obviously, if you eventually can explain the differences
using more mechanistic covariates than study number that is of more use.







Received on Wed Jun 17 2009 - 16:43:28 EDT

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