Dear NM user group:
Please change my address from ga...@emory.edu to ghaziaa...@yahoo.com.
Sincerely,
Ghazia Asif, PhD
Emory University
Mark, Douglas,
The Akaike Information Criterion is more general, so is (should be?) applicable
to $OMEGA changes as well.
The addition of off-diagonal elements may be treated more liberal as far as I
am concerned. I personally focus more on the simulation properties than how
much the ofv drop
Mark,
Glad that we end up with the same advice ;-).
But even if the estimates of the diagonal elements increase a bit, it
does not mean that the total spread in the predictions increases. To
illustrate that I have written an R script that samples from a 2-by-2
matrix and simulates a bundle of e
Folks:
Much thanks for all of the feedback.
Mahesh, I agree with your comments below. In the mild to moderate AD
population at least, as these works point out, it is likely that the
biomarker endpoints may have maxed out, years, perhaps decades prior in
some cases. It may be that we can show a
Hello Brian,
1) Is the meeting in New Jersey? If not, you got a deal ;-)
2) Did the HA specifically request optimization of a weighted score/utility
index? Sounds to me as if they are merely asking you to assess probability
distributions (alpha level, power to reject null hypothesis or the like
Dear Dr. Corrigan,
Could you kindly elaborate what is the other co-primary end-point? I can
understand that you may not be able to share this additional
information. I will therefore try to illustrate my concern with this
secondary end-point optimization assuming that your drug of interest is
an a
Title: Block versus diagonal omega
Brian, Let me risk ridicule and mention my favorite algorithm, Genetic algorithm. We've actually done some work in this area (just a little, not published anything). But, it is pretty easy to set up an optimization with constraints. Basically, you simulate (
