Bioequivalence and Bioavailability Forum

Hi ElMaestro!

❝ I am fiddling a bit around with scaled BE and trying to use R for same.

Welcome to the crippled model!

❝ Ad 1:

❝ Looks to me like the lm allows effect estimates for 75 subjects; this means subjects with a missing value are not tossed out. So I guess all is fine with 77 in total; seemingly 38 and 39.

Wonderful. Phoenix/WinNonlin by default uses all data as well (REML…). Since we have to mimick SAS we have to get rid of subjects with incomplete data (#24, 31, 67, 71). The complete data set contains 73 subjects with two administrations of R.

❝ Ad 2:

❝ For df I tried both the df form the full model and from the Ref-only model (let me add: I think it is a valid argument that the df from the latter should be used but I am sure we can have a good fight over that some other time).

Yep. 71.

❝ A=read.table("EMAset1b.csv", header=T)

Can you post your EMAset1b.csv? Since my crystal ball is at the laundry I can’t check your code.