RE: Models that abort before convergence Addendum
Leonid, Let me understand: You now have a theory that the way to determine whether the NONMEM error messages are useful (i.e., they tell you something about the model "goodness") is a poll. This, I think is a theory (and one well established in epistomolgy) of how to find an optimal solution - appeal to a large number of presumably well informed people. As data that may be relavant to this theory, I would point out that a poll gave us GW Bush as our 43rd president. Nick, in contrast has suggested that the error messages could be used as a source of random numbers. This also, I think, is a theory without data to support or contradict it. So .... Let me propose a solution - let's generate some data. Suppose we randomly generate 1000 models. We could tests the hypotheses: Are the error messages random (I suspect they are not, that there is some information in them). To test this, see if the error messages are predictive of other (presumably non-random) measure of goodness - NPC and NPDE, and perhaps PPC come to mind. Do the error messages provide information not readily available in NPC, NPDE and PPC. Not really sure how to test this, without some "gold standard" of goodness, except perhaps to compare the different measures to the model that was used to simulate the data (seems like measures based on that would be "correct" in some way??). I need some ideas on this. I can generate, run and extract results from random models (using the GA software) - I already have NPDE and PPC in it, was thinking of adding NPC. Any interest/collaborators?? Mark Sale MD
Next Level Solutions, LLC
www.NextLevelSolns.com
919-846-9185
Quoted reply history
-------- Original Message --------
Subject: Re: [NMusers] Models that abort before convergence Addendum
From: Leonid Gibiansky <[EMAIL PROTECTED]>
Date: Thu, November 20, 2008 9:57 pm
To:
Cc: nmusers < [email protected] >
Nick, Mark, and All,
We can argue indefinitely, but let me propose a poll. If you like to
participate, reply directly to me (use "reply", not "reply to all"). I
will summarize all the replies received up to the end of November. Skip
the questions that you do not like to answer, write NA if the question
is not applicable. Summaries will be blinded.
1. Would you like Nonmem to stop producing all run-time (not syntax)
error/warning messages (134, 137, number of significant digits, etc.)
and "MINIMIZATION SUCCESSFUL" messages (YES/NO):
2. Do you remember at least one example when the run-time error message
helped you to find an error in your code (YES/NO):
3. In your experience, run-time error messages allow you to detect model
errors or problems quicker than it would be done without error messages:
(agree/disagree)
4. Have you ever used in your report/publication ANY model that did not
have $COV step completed (YES/NO):
5. Have you ever used in your report/publication ANY model that did not
converge (YES/NO):
6. Have you ever used in your report/publication FINAL model that did
not have $COV step completed (YES/NO):
7. Have you ever used in your report/publication FINAL model that did
not converge (YES/NO):
8. Define yourself as novice/intermediate/experienced Nonmem user:
Thanks
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566