SAS vs Winnonlin [Software]

posted by jag009  – NJ, 2013-07-25 00:56 (4349 d 20:24 ago) – Posting: # 11055
Views: 18,469

Hi Helmut,

❝ Some ideas:

Conventional 2×2 cross-over: Since Phoenix/WinNonlin only speaks REML, you have to exclude incomplete data. Unlike in SAS GLM (which ignores such cases) you have to filter for complete data in Phoenix first. Otherwise you are in mixed-effects model limbo. For the EMA you have to treat all effects fixed. In Phoenix that means: Delete subject(sequence) in the variance structure / random1 tab and add it to the fixed effects.

Higher-order Xover (say two references). Same as above, but for the EMA you have to exclude the “uninteresting” treatment, while for the FDA I guess (!) you keep all in the model and report only the relevant pair. That’s independent from the software you use.


It is a 3-way 2 test vs reference study (tada! You guessed it! We have common/pool variance!)
Well the data I have is not complete, one subject is missing period 3 (withdrew) but I elected to keep his periods 1 and 2 data since period 2 was the reference arm. I used GLM in SAS and then for my own amusement I ran the data in Phoenix...

John

Complete thread:

UA Flag
Activity
 Admin contact
23,424 posts in 4,927 threads, 1,671 registered users;
48 visitors (0 registered, 48 guests [including 9 identified bots]).
Forum time: 21:20 CEST (Europe/Vienna)

Medical researches can be divided into two sorts:
those who think that meta is better and those
who believe that pooling is fooling.    Stephen Senn

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz
HTML5