Discussion on “Optimal test procedures for multiple hypotheses controlling the familywise expected loss” by Willi Maurer, Frank Bretz, and Xiaolei Xun

Yoav Benjamini*, Ruth Heller, Abba Krieger, Saharon Rosset

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We discuss three issues. In the first part, we discuss the criteria emphasized by Maurer, Bretz, and Xun, warning that it modifies the per comparison error rate that does not address the concerns raised by multiple testing. In the second part, we strengthen the optimality results developed in the paper, based on our recent results. In the third part, we highlight the potentially important role that the use of weights may have in practice and discuss the difficulties in assigning weights that convey the importance in the gain and loss functions, especially as it pertains to multiple endpoints.

Original languageEnglish
JournalBiometrics
DOIs
StateAccepted/In press - 2023

Keywords

  • familywise error
  • most powerful test
  • multiple end-points
  • per comparison error-rate
  • sample size determination
  • strong control

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