## Missings [General Sta­tis­tics]

Dear Shuanghe!

» ... By FDA's code, all subject has to complete all 4 periods. so In practice, number of subjects having T data is always equal number of to subjects having R data.
»
» By the way, I asked FDA about possibility of modify the code to include subject with 2 R and 1 T and for "ilat", the mean difference between T and R, use the modified version:
» ilat = lat1t - 0.5*(lat1r+lat2r) ,
» where lat1t could be replaced by lat2t depending on period of dropout. It should be easy to implement with IF/ELSE/THEN. Buy they confirmed 1 and a half years later that subjects should have data of all 4 periods and reject the suggestion.

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

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?

Regards,

Detlew