Zheng,
I think you are imagining a problem that does not really exist. Each
observation contributes something to the overall fit. There is no
intrinsic reason to require "balance" across subjects. It is always
useful to have more information but it is not a good idea to remove
observations.
Best wishes,
Nick
On 06-Jan-16 15:03, Zheng Liu wrote:
Dear all,
I recently have a data set for pk parameters fitting. The issue is
some patients have far more measurement points than others (i.e. a few
patients have ~15 points, other patients have only 1 or 2). I
speculate in the fitted parameters, those patients with many points
would contribute much more than those with less points. Then the
population "average" values of fitted pk parameters are not
anymore average from all the patients, but more biased to those
patients with many points. This is not what I expect.
Of course I could take away some points from the patients with many
points, in order to be comparable to less-points patients. Then I
will be forced to lose some information from the data set. I just
wonder are there anyone who have better proposal to solve this
problem? I appreciate your help very much!
Best regards,
Zheng
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53
email: [email protected]
http://holford.fmhs.auckland.ac.nz/
"Declarative languages are a form of dementia -- they have no memory of events"
Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A, Pypendop,
B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite pharmacokinetic models
- tests of assumptions and predictions. Journal of Pharmacology & Clinical
Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin
Pharmacol. 2015;79(1):18-27.
