Bioequivalence and Bioavailability Forum

Dear ElMaestro,
Thank you for your persistent concerning on my post.

❝ My problem is I cannot see what you are trying to achieve.

My only and final purpose is to manually calculate SEs and CIs of R and T in BE analysis both for equal and unequal balances data (situation of incomplete data is beyongd my ability), may be we can called it "post-BE estimation".

❝ For my learning purposes and/or your consideration:

❝ 1. Why would you use PROC MIXED when not specifying a random effect?

I used PROC MIXED without a random effect with only purpose of try-and-see what will we get with such a unusual method. But not to recommend this in BE analysis.

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

❝ 2. Do you know what the documented behaviour of PROC MIXED is when no random effect is specified? There is an example in the online manual but it does not tell what the general behaviour is.

I really want to know, but Google gives me no concrete answer. May be it is too complex to list all the calculation steps in Proc Mixed, but I really want to manually calc SE and CI. You know many programs are able to handle matrix and var-covar matrix, so I think it is possible but might be time-consuming, and unfortunately, no one can tell me how to do it.

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?
Without use of WNL or SAS or other software with similar function, we cann't get it?

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?

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

Again, thank you for your attention.