Properties of multiple intersection-union tests for multiple endpoints in combination therapy trials

Peter H. Westfall, Shu Yen Ho, Barbara A. Prillaman

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

We consider intersection-union tests involving multiple endpoints in a combination drug trial, for which we control the familywise error rate in the strong sense using closed testing methods. Bonferroni-Holm, Simes-Hommel, and Resampling-Based methods all are considered in this context. Familywise error rate control heuristics are developed and evaluated using a simulation study that is specifically tailored to the intersection-union setting. Both Resampling-Based and Simes-Hommel uniformly outperform the Bonferroni-Holm. Using simulations of power, the choice of Simes-Hommel versus Resampling-Based is seen to depend on the particular alternative of interest. Because it is simpler and has generally good power, we recommend the Simes-Hommel intersection-union tests. The techniques are illustrated using real data from a clinical trial to evaluate a combination asthma therapy.

Original languageEnglish
Pages (from-to)125-138
Number of pages14
JournalJournal of Biopharmaceutical Statistics
Volume11
Issue number3
DOIs
StatePublished - 2001

Keywords

  • Adjusted p-value
  • Bonferroni inequality
  • Closed testing
  • Familywise error rate
  • Multiple endpoints
  • Resampling-based multiple testing
  • Simes test

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