CVwR ~ CVwT ~ CVw? [Power / Sample Size]

posted by zizou – Plzeň, Czech Republic, 2017-07-08 17:29 (2455 d 16:55 ago) – Posting: # 17523
Views: 6,885

Hi everybody and nobody!

❝ I agree with ElMaestro. If you design a replicate study based on the CVw of a 2×2×2 crossover you have to assume that CVwT = CVwR.


Practically I agree with everyone of you.
Nevertheless I have one nitpicker's question.
We have to assume CVwT = CVwR = CVw? (If we design a replicate study for EMA based on the CVw of a 2×2×2 crossover.)
Or CVw can't differ when CVwT = CVwR?
Theoretically I can imagine (no real) data of 2x2x4 replicate study - see following idea:
After Test treatment we will have almost the same values for each individual subject (e.g. subject No. 1 value 0.9501 after the first T and 0.9502 after the second T (before ln-transformation)) - for simplicity geometric mean of T values close to 0.95.
In the same way after Reference treatment we will have almost the same values for each individual subject (e.g. subject No. 1 value (1/0.9501) after the first R and (1/0.9502) after the second R (before ln-transformation) - If all the values of R are reciprocal values of T we should get the same intra-subject CV for T and R.) - for simplicity geometric mean of R values equal to (1/0.95).
So GMR T/R of all "pooled" data will be close to 0.95/(1/0.95)=0.95^2=0.9025 and CVw used for CI calculation will be higher than CVwT and CVwR?
I know, in this kind of example the CVwT and CVwR are extremely low, but the point is that theoretically the CVw observed in 2x2 study can be higher than 30% (so we can try replicate design with possible widening of BE acceptance criteria) but the CVwT and CVwR (which we don't know from 2x2) can be lower.
Fact or Fiction?

Best regards,
zizou

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