one option is to use BASE and KOUT as primary parameters and compute
KIN=BASE*KOUT
Then one can either fix BASE=(observed base) or use
BASE=(observed base)*EXP(ETA())
to account for the random noise of observations.
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
On 7/27/2015 2:39 PM, Zhao,Li wrote:
Dear NMusers,
Right now I am doing covarite analysis for an indirect response model.
I tested a few potential covarites and found it's STATISTICALLY
significant if I add *observed baseline valu*e to *kin*.
But I am not sure if it makes sense to add t/he baseline value/ as a
covarite to /kin/.
Could you please help me if you have had similar experiences before?
Thank you very much!
