Potvin method B subtleties [Two-Stage / GS Designs]

posted by jdetlor – 2011-02-02 17:08 (5254 d 06:57 ago) – Posting: # 6545
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Dear D. Labes,

❝ The ratio of subjects between both stages is always not known at the planning stage in methods with interim sample size adaption. Therefore this is also true for the Potvin et.al. methods.


I agree with this. What I was driving at was the sequential analysis side. Traditionally the time points are specified before hand (equally spaced or not) and the values for alpha can be calculated.

❝ Using any scheme of nominal alpha values from the classical group-sequential designs is therefore not exactly correct because they rely on same number of subjects in each stage and the impact on the overall alpha has to be shown.


True, and I believe this part is what Potvin et al. were exploring — Is there a value for alpha that would maintain an appropriate type I error rate over both stages. I would point out that Gould in his paper discusses different ratios, not just where the ratio of subjects between stages is 1:1.

❝ To express my question more precisely: The power calculation in Method B is done in case of non-BE evaluated at alpha=0.0294. Eventually this is superfluous because if using the point estimate will result always in a power below that desired?


I'm still not sure I follow. Are you concerned about the use of a reduced alpha (0.0294) for the power calculation, or is it with using the point estimate instead of GMR=0.95? We may or may not have less power than initially calculated due to the new variability estimate from stage 1 (using the same GMR=0.95).

❝ Needs to be shown if this is true also for cross-over designs aimed to evaluate equivalence.

❝ Do you know any 'non-naive' application?


Agreed. But this depends on your definition of 'naive' :-D

❝ My concern was that Method C has the possibility to evaluate the data at stage 1 with alpha=0.05 if the power was great enough, i.e. without paying any penalty.


❝ I know Helmut prefers Method C and has already convinced the German BfARM

❝ :cool:.

❝ This would also my preferred choice according to the reasoning of Potvin et.al. in their recommendations "Another advantage of method C is that it is designed so that if the study were found to have adequate power at the first stage, the alpha for that study would be the same as if it were designed to be single-stage". Why to pay a penalty for repeated testing, if no repeated tests are applied?


My thoughts as well.

❝ Any experience other then Helmut's?


Sorry, nothing to add. :-(

However, if you are looking for a small number of subjects up front and a small value for alpha for evaluating BE at stage 1, you could use Gould's method. This is provided you know the maximum number of subjects you will enroll (not adaptive), and this maximum number with cover a reasonable amount of variability.

J. Detlor

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