| Multiplicity is a well established notion in statistics that arises when simultaneously testing n ≥ 2 hypotheses. To combat this issue, over time, numerous multiple comparison procedures have been developed. Such methods are relied upon heavily in confirmatory clinical trials, both in dose-finding and multiple-endpoint scenarios. The proposed procedure is a hybrid between the data-driven Weighted Holm procedure and the Fallback procedure which relies heavily on the a priori ordering of the hypotheses based on weights. Strong control of the familywise error rate is proven. Both general and previous clinical examples are performed utilizing this new method while comparing the outcomes to those of other techniques. Simulations test the proposed procedure against the Weighted Holm and the Fallback with varying weighting schemes and numbers of hypotheses. The results provide evidence that the proposed procedure outperforms the Weighted Holm in a multitude of scenarios while becoming increasingly competitive against the Fallback for larger n.. |
