Re: Centering (was Re: Missing covariates)
Date: Thu, 05 Jul 2001 10:08:11 -0400
From: Alan Xiao <Alan.Xiao@cognigencorp.com>
Subject: Re: Centering (was Re: Missing covariates)
Hi, folks,
I think I should clarify my question like this:
1). Assuming you are creating a graph of concentration-time profile for
a population with measured concentrations and PRED of the model, should
the PRED of the structural model predict the Mean concentrations or
Median concentrations , or neither ?
2). Assuming you have a final model with all significant non-centered
covariates, if you want to reduce this model to the structural model,
should you set each covariate at its mean value or median value, or
something else? Or in this way: Assuming you have a final model with
all significant non-centered covariates, if you want to predict (by PRED
of this model) what the structural model predicts (by PRED), should you
set each covariate at its mean value or median value, or something
else? (Please don't tell me to set all coefficients of covariates at
zero).
About 2). If you say MEDIAN, here is my follow-up question, how can you
use MEDIAN for a categorical covariate ?. If you use MEAN, is this MEAN
over IDs or over concentration records? (Note that all PK parameter
estimates are "regulated" by measured concentrations, not by measured CL
or Vs).
About the expression of a model, I am not against the "standardization"
at 70 KG (weight) or whatever for the purpose of practice. However, as
a strict scientific principle, the expression of a model or any
analysis should strictly (and as explicitly as possible) reflect the
TRUE information that the model is based on. For readers/customers who
don't have the detail knowledge about how and why the model has been
developed, they are easily misled to the point that the model with
expression of CL = THETA1 + THETA2*(AGE-65) be developed from data
with MEAN age of 65 plus some SE (especially when CENTERING concept is
implied) while the real measured data (for the model development) are
averaged at age of 50 plus some SE, if you artificially shift the
"centering" from 50 to 65. Another physician might think that, OK,
since the model has been developed from a population with mean age of 65
(which is not true), I can still use it for an 85 years old patient.
But actually, this might be beyond the limit that the original data can
reasonably support.
I think, a lot of work need be done to bridge the PKPD scientists and
clinical professionals. But I hope application won't twist what science
(if it could be labeled as science) really looks like.
Thanks,
Alan.