Missings [General Sta­tis­tics]

posted by Shuanghe  – Spain, 2015-09-30 17:34 (3102 d 17:21 ago) – Posting: # 15502
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Dear Detlew,

❝ What you describe is the part of the SAS code concerning (µT-µR)^2 of the linearized scABE criterion (ilat analysis).


You are right.

❝ For the part dealing with intra-subject variability the Progesterone / warfarin guidance SAS code (dlat analysis) does not automatically drop subjects having missings under Test treatment.


Yes. And I tried both with some of my studies. The difference is small but in borderline case it could mean pass or fail BE

❝ What to do here? Retain subjects having 2R, but only 1T or 0T? Or also drop them as we have done in the R code in the post below?


In addition to the scenarios you mentioned, what about subject with 0R + 2T? Theoretically they can provide information on ISCV for T.
To make a list of what cannot be included is much easier,
All the rest combinations can provide ISCV either for T or for R or for all.

So, for the moment I prefer using subjects with all 4 periods just to be safe (provided it was properly described in the protocol). Otherwise, situation would be more complicated.

All the best,
Shuanghe

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