mamidi.ganesh ● 2006-09-23 10:41 (6802 d 12:54 ago) Posting: # 256 Views: 20,551 |
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Hai to all, Can anybody tell me how to approach with ANOVA in a 3x3 crossover Bioequivalence study. In the above design can we use Linear model or Mixed model or both by using SAS. Any information or references regarding 3 way crossover kindly let me know. Thanks Ganesh |
Jaime_R ★★ Barcelona, 2006-09-23 19:34 (6802 d 04:01 ago) @ mamidi.ganesh Posting: # 257 Views: 17,378 |
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Hi Ganesh, PROC GLM is for complete data (subjects completed all treatment periods), whereas PROC MIXED is for incomplete (some data are missing), irrespective of the number of treatments. GLM uses an exact solution, whereas MIXED is iterative; if you have complete data you may use both of them - although GLM is of course faster. ![]() Hope, that helps. BTW, what do you mean by 3x3? — Regards, Jaime |
mamidi.ganesh ● 2006-09-25 12:28 (6800 d 11:07 ago) @ Jaime_R Posting: # 258 Views: 17,034 |
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Hi Jaime, Thanks for u r reply. By the way 3x3 means three treatment three period. can u please suggest me any books or reference sites about this topic. |
Jaime_R ★★ Barcelona, 2006-09-25 13:12 (6800 d 10:23 ago) @ mamidi.ganesh Posting: # 260 Views: 16,924 |
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Hi Ganesh, ❝ Thanks for u r reply. You are welcome ![]() ❝ By the way 3x3 means three treatment three period. ❝ Can u please suggest me any books or reference sites about this topic. I hope you are planning for 6 sequences! For an explanation and references see Helmut's post. — Regards, Jaime |
Helmut ★★★ ![]() ![]() Vienna, Austria, 2006-10-03 14:49 (6792 d 08:46 ago) @ mamidi.ganesh Posting: # 268 Views: 19,433 |
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Hi Ganesh, the SAS-application 'EquivEasy' may be helpful. A description *) and authors' contact details can be downloaded here.*) V Luzar-Stiffler and C Stiffler Equivalence testing the Easy Way J Comp Inform Technol - CIT 10, 2002, 3, 233-239— Dif-tor heh smusma 🖖🏼 Довге життя Україна! ![]() Helmut Schütz ![]() The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes |