The Haybittle–Peto boundary is a rule for decidi
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Posted On: 01/08/2021 11:03:58 AM
The Haybittle–Peto boundary is a rule for deciding when to stop a clinical trial prematurely.[1] It is named for John Haybittle and Richard Peto.
The Haybittle–Peto boundary is one such stopping rule, and it states that if an interim analysis shows a probability of equal to, or less than 0.001 that a difference as extreme or more between the treatments is found, given that the null hypothesis is true, then the trial should be stopped early. The final analysis is still evaluated at the normal level of significance (usually 0.05).
It appears that yes, our s/c trial was not halted at 50% nor at 75% interim analysis, but it was not because at those times, our p value did not achieve 0.05 but rather, the trial was not halted, because we did not achieve 0.001
Thus, it it quite conceivable that at 50% and/or at 75% interim analysis, that we did achieve 0.05 p value or better, just not 0.001
The Haybittle–Peto boundary is one such stopping rule, and it states that if an interim analysis shows a probability of equal to, or less than 0.001 that a difference as extreme or more between the treatments is found, given that the null hypothesis is true, then the trial should be stopped early. The final analysis is still evaluated at the normal level of significance (usually 0.05).
It appears that yes, our s/c trial was not halted at 50% nor at 75% interim analysis, but it was not because at those times, our p value did not achieve 0.05 but rather, the trial was not halted, because we did not achieve 0.001
Thus, it it quite conceivable that at 50% and/or at 75% interim analysis, that we did achieve 0.05 p value or better, just not 0.001
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