Dear All,
I know this is an old topic, too, but would like to see the statistics.
When you have a dataset with about 10% of dense Phase II data (predose, 2, 4,
8, and 12 hrs post dose on day 1 and at steady state, twice-daily dose regimen)
and about 90% of very sparse Phase III data (1-2
Hi Alan,
Here:
http://quantpharm.com/pdf_files/PAGE_2008_Poster_1268_web.pdf
I used all datasets that I had, and I was not able to find any problem
where FO was superior to FOCE.
Not-converged FOCE is better, in my opinion, than converged FO (although
you can always check using diagnostic
There's an additional, related point to consider with respect to
estimation method, in selecting a simultaneous vs sequential
approach
In the case where simultaneous modeling under conditional estimation
is not feasible (run-time, convergence, etc), it is preferable to use
a
PROTECTED] On
Behalf Of Gastonguay, Marc
Sent: Tuesday, December 09, 2008 1:56 PM
To: Gibiansky Leonid; Xiao, Alan; Hussein, Ziad; nmusers nmusers
Subject: Re: [NMusers] FO vs FOCE, sequential vs simultaneous
There's an additional, related point to consider with respect to estimation
method
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From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Gastonguay, Marc
Sent: Tuesday, December 09, 2008 7:56 PM
To: Gibiansky Leonid; Xiao, Alan; Hussein, Ziad; nmusers nmusers
Subject: Re: [NMusers] FO vs FOCE
Alan,
When the answers are known (i.e. the data is simulated) then FOCE is
always superior to FO. Whether the run converges or not make no
difference to the final model parameters.
I always use FOCE. I only use FO for teaching because of quicker run times.
If you want the wrong answer
Leonid,
Thanks very much for this experimental data support confirming again the
wisdom of using FOCE rather than FO and not worrying about convergence.
Nick
Leonid Gibiansky wrote:
Hi Alan,
Here:
http://quantpharm.com/pdf_files/PAGE_2008_Poster_1268_web.pdf
I used all datasets that I
