Let's say I have a set of hypotheses ordered in time. These are about comparison to some baseline moment: $H_{t1 vs. baseline}$, $H_{t2 vs. baseline}$, $H_{t3 vs. baseline}$, ...
I have 10 time points, thus, 10 hypotheses. I want to find the first consecutive three statistically significant ones. Something like this:
H1 - not sign
H2 - sign *** THIS
H3 - sign *** THIS
H4 - sign *** THIS
H5 - not sign
H6 - not sign
H7 - sign
H8 - sign
H9 - sign
H10- sign
There are various multiple comparisons methods, e.g. Dunnett. But I want to stop after the first occurrence. I don't care of the subsequent ones. So, I don't want to "penalize" my significance level too much from the start.
I want to start with the first set (H1-H3), check it at $\alpha=0.05/3$, then, if not found expand it by the next hypothesis (H1-H4), check it at $\alpha=0.05/4$ , and continue until success or full set (H1-H10) examined.
So, at each run, the FWER is controlled. But what about the overall FWER? I make a decision on going to the next step based on the previous one ("Didn't find").
Do I need also to adjust each step?
I mean:
Step 1: H1 - H3, α=0.05/3 (3 comparisons)
Step 2: H1 - H4, α=0.05/4 and also ÷2, as this is 2nd run, so it gives α=0.05/8
Step 3: H1 - H5, α=0.05/5 and also ÷3, as this is 3rd run, so it gives α=0.05/15
This allows me to find the difference earlier, but at each step, the penalty gets horribly large ($\alpha=0.05/15$ at 3rd run), testing only 5 hypotheses (and the first 3 are already non-rejected!).
Should I adjust twice or not, in your opinion?