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General question on modeling

From: Mark Sale - Next Level Solutions <mark>
Date: Mon, 19 Mar 2007 11:32:54 -0700

Dear Colleagues,
   I've lately been reviewing the literature on model building/selection
algorithms. I have been unable to find any even remotely rigorous
discussion of the way we all build NONMEM models. The structural
first, then variances/forward addition/backward elimination is
generally mentioned in a number of places (Ene Ettes in Ann
Pharmacother, 2004, Jaap Mandemas series on POP PK series J PK Biopharm
in 1992, Jose Pinheiros paper from the Joint Stats meeting in 1994,
Peter Bonates AAPS journal article in 2005, Mats Karlsons AAPS
PharmSci, 2002, the FDA guidance on Pop PK). It is most explicitly
stated in the NONMEM manuals (Vol 5, figure 11.1) - without any
reference. From the NONMEM manuals it is reproduced in many courses,
and has become axiomatic. I've looked at the stats literature on
forward addition/backwards elimination in both linear and logistic
regression, where it is at least formally discussed (with some
disagreement about whether it is "correct"). But, I am unable to find
any justification for the structural first, then covariates (drive by
post-hoc plots), then variance effects approach we use (I'm sure many
people will point out that it is not nearly that linear a process,
although in figure 11.1, Vol 5 of the NONMEM manuals, it is depicted as
a step-by-step algorithm, without any looping back). Can anyone point
me to any rigorous discussion of this model building strategy?

Mark Sale MD
Next Level Solutions, LLC

Received on Mon Mar 19 2007 - 14:32:54 EDT

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