Simulating the data is only part of a VPC. The other part is describing
the distribution of the actual observations. If data is collected
honestly with actual sampling times then of observation times will be
different for every subject whether or not the protocol also had some
random element.
A solution to this is to bin the observed (and simulated) values around
some suitable times e.g. using nominal protocol times or with more
complex algorithms (see Lavielle et al. 2011). Then the distribution of
observations and simulations can be compared at each of those times.
Lavielle M, Bleakley K. Automatic data binning for improved visual
diagnosis of pharmacometric models. J Pharmacokinet Pharmacodyn.
2011;38(6):861-71.
On 11/01/2012 11:44 a.m., indrajeet singh wrote:
you could try creating uniformly distributed time points in a new data
set covering the whole time range in your observed data set and repeat
the simulation for 100-200 times for 100 subjects or whatever number
you think is reasonable for your study population size. New data set
can be easily created in R using few lines of codes.
Best
Jeet
On Tue, Jan 10, 2012 at 4:11 PM, Ayyappa Chaturvedula
<[email protected] <mailto:[email protected]>> wrote:
Dear expert users,
I am working on a dataset where subjects were sampled at different
visits at random. I have developed a model for the data but not
sure how to do a VPC as they do not have the same sampling
scheme. I appreciate some guidance in this.
Regards,
Ayyappa
--
Indrajeet Singh,PhD
Sr. Clinical Pharmacokineticist
Abbott Labs, North Chicago, IL
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology& Clinical Pharmacology, Bldg 505 Room 202D
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
tel:+64(9)923-6730 fax:+64(9)373-7090 mobile:+64(21)46 23 53
email: [email protected]
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
