Geometric mean and CV [Power / Sample Size]

posted by Helmut Homepage – Vienna, Austria, 2019-09-06 18:15 (694 d 09:11 ago) – Posting: # 20549
Views: 4,512

Hi Rocco,

» So basically your analysis follows from the fact that the variance of the difference of T and R equal the sum of the variance of T and the variance of R, correct?

Well, you have four variance components (s²wR, s²wT, s²bT, s²bR). Then
  1. Full replicate designs
    All are identifiable.
  2. 2×2×2 crossover (balanced and complete for simplicity – otherwise, weighting is required)
    s²w = (s²wR + s²wT)/2 and s²b = (s²bT + s²bR)/2.
  3. 2 group parallel
    Only the pooled (total) s²p. With a tricky mixed-effects model you could get s²pT and s²pR.
  4. One treatment (FIM)
    Only s²p.
Hence, if you want to plan #3 based on #4 you have to assume that the variances (within, between) of T and R are at least similar. ;-)

» And you are using the geometric CV as the estimate of CVp for R?

Yes.

Dif-tor heh smusma 🖖
Helmut Schütz
[image]

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes

Complete thread:

Activity
 Admin contact
21,596 posts in 4,516 threads, 1,532 registered users;
online 2 (0 registered, 2 guests [including 2 identified bots]).
Forum time: Sunday 03:26 CEST (Europe/Vienna)

Sit down before fact as a little child,
be prepared to give up every conceived notion,
follow humbly wherever and whatever abysses nature leads,
or you will learn nothing.    Thomas Henry Huxley

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz
HTML5