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RE: General question on modeling

From: Mark Sale - Next Level Solutions <mark>
Date: Tue, 20 Mar 2007 10:08:10 -0700

My last email on this - I promise.
  I actually did ask Lewis this, maybe 8 years ago when I first started
thinking about this. He did not have any reference for the algorithm,
other than the literature on forward-addition in linear and logistic
regression. He said (as best I remember) "None that I know of, but so
far it seems to work pretty well, and there isn't anything else". I
asked Stuart as well, but not sure I really got an answer. It does seem
to be intuitive - especially since, my view is that time is by far the
biggest contributor to variability, to work first on the structural
model (which attempts to explain away the effect of time). Interesting
insight from Allison on why the variance terms ended up last in the


Mark Sale MD
Next Level Solutions, LLC

> -------- Original Message --------
> Subject: Re: [NMusers] General question on modeling
> From: "Alison Boeckmann" <alisonboeckmann
> Date: Tue, March 20, 2007 12:44 pm
> To: "Mark Sale - Next Level Solutions" <mark
> Cc: nmusers
> Dear nmusers,
> I'd like to add a historical perspective. Mark's original question that
> started this discussion had to do with Fig. 11.1 of the NONMEM Users
> Guide Part V. The chapter on Model building was written by Lewis
> Sheiner, and was pretty much identical to his corresponding lecture in
> the NONMEM short course. This dates it to approx. 1984. Did Lewis have
> any rigorous reason for presenting this approach, or did it seem "right"
> to him? He was a great intuitive thinker. The only way to know what
> was in his mind at the time might be to 1) check the literature as of
> that time, and 2) ask the people who were fellows at that time. But
> remember that early NONMEM users were constrained by very slow
> computers. To work with large models was prohibitively costly, so there
> was good reason to stay with a simple structural model and only add
> intraindividual (ETA) effects later, because they added so much to the
> compute time. There may not have been much literature on this strategy
> because (so far as I understand) Sheiner and Beal were among the first
> to do modelling with both intra and inter individual random effects, and
> there was not much in the way of software for it before NONMEM.
> On Mon, 19 Mar 2007 11:32:54 -0700, "Mark Sale - Next Level Solutions"
> <mark
> > 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
> >
> >
> >
> --
> Alison Boeckmann
> alisonboeckmann
Received on Tue Mar 20 2007 - 13:08:10 EDT

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