RE: BOV
From: "Kowalski, Ken"
Subject: RE: [NMusers] BOV
Date: Thu, September 23, 2004 12:46 pm
Hi Diane,
My experience and intuition (we know it can be faulty so take it for what
its worth :-)) and experience says that misspecification of the variance
structure often has little impact on the accuracy of the theta estimates.
However, misspecification of the variance structures could impact the
precision of our estimates and hence could lead to statistical tests (e.g.,
likelihood ratio tests) that don't preserve nominal type I errors. I agree
with Mats that correlation in the residuals over time (autocorrelation) is
probably the more important time effect to be concerned about in this
regard.
As you know I'm a proponent of building full models whether they be fixed or
random effect parameters. With respect to the omega structure I tend to
build the largest structure that is supported by the data. I don't worry
about being parsimonious in omega unless
over-parameterization/ill-conditioning dictates it. Thus, following that
same strategy for BOV estimation I certainly plan to start looking at
estimating the individual BOVj. I agree that in many cases it may be
parsimonious to constrain BOVj=BOV (BLOCK SAME) but as Mats has pointed out
one might see differences in BOVj when some occasions are spaced further
apart. For example, if two occasions are spaced close together but a third
is much more distant in time, a parsimonious model may be to constrain
BOV1=BOV2=BOV and estimate a different BOV3 for the third occasion.
However, in this setting I'm inclined to just estimate a separate BOVj for
the three occasions as long as the data support it (i.e., the model is not
ill-conditioned). I don't get hung up on formal testing of the variance
structure and primarily rely on patterns in the omega structure (even for
failed full block omega runs) to help guide my choice of a parsimonious
omega when needed. I realize that a lot of attention to omega may not be
warranted when the main interest is in a population mean prediction (say for
dose selection) but I've found that I never know when I might use a
previously developed model for other purposes such as clinical trial
simulations where greater attention to omega (including BOV estimation)
might be warranted.
Ken