Bioequivalence and Bioavailability Forum

Hi yicaoting,

❝ BTW: After my tries, I know that if we use WNL's default settings in BE Wizard, it is impossible get identical result from SAS， here so called identical result includes: LSMs and its SEs and CIs for R and T, and 90% CI of difference. Thus, maybe it is time to modify WNL's default setting or to suspect SAS? I am really

Helmut informed us that WNL used a default Mixed model even for a 2,2,2-BE evaluation. That could be why you don't get the same result. At the end you need to ask yourself: Do I wish to include subjects in my 2,2,2-BE analysis which have a missing period? If you answer is yes, then use a mixed model. If your answer is no, use a linear model (or delete the subjects in question and do the mixed, same thing).

❝ All in one, even if let's stop the game of Proc Mixed or Proc GLM, is it possible to manually calculate CI of PKmetrics for R and T in 2*2 crossover design?

No, it is perfectly possible to calculate a CI 'manually', as long as you want to reproduce the CI you get from GLM (but not MIXED, case of missing values in a period makes the difference). Look up the equations in Chow & Liu's book; I don't have it here.
Edit: You can also look up the equations in Potvin et al. Pharm. Stat. 7:245–262.

❝ Another Issue: I know that in NSCC 2007's TOST analysis, SEs for R and T are different, and I have derived it's calculation step, it uses pooled SE from datesets of two sequences for each treatment. Although it does not give out CI, it can be easily calculated using LSMean+/- T*SE. From a personal view, I think different SEs for R and T is more reasonable than the same SEs. What's your opinion?

My opinion is that in a 2,2,2-design we do not have true replication of Test or Reference. Therefore we cannnot calculate within-subject-variabilities for T or R. We can calculate it for the difference. We can also derive the variability for the between-subject variability for T and R, and we can possibly even do that individually if we have a reason to do so (but don't ask me how; I don't know). So if you are looking for SE's corresponding to intra-subject variability for T or R, look no further until you have a replicated study.

❝ Thus, which CI is true or acceptable? SAS's (same as WNL's) or NCSS's?

There is no true or false. As another example, look up on the www the heated discussions around type I, II and III sums of squares. There is a lot of personal preference and religion involved here. Some of it is written in the form of guidelines. As you saw from an earlier post by Helmut, the EU guideline now asks for subject as fixed factor. If you can accept that as your golden standard then there's your answer.