On using the bootstrap for multiple comparisons

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

There are many ways to bootstrap data for multiple comparisons procedures. Methods described here include (i) bootstrap (parametric and nonparametric) as a generalization of classical normal-based MaxT methods, (ii) bootstrap as an approximation to exact permutation methods, (iii) bootstrap as a generator of realistic null data sets, and (iv) bootstrap as a generator of realistic non-null data sets. Resampling of MinP versus MaxT is discussed, and the use of the bootstrap for closed testing is also presented. Applications to biopharmaceutical statistics are given.

Original languageEnglish
Pages (from-to)1187-1205
Number of pages19
JournalJournal of Biopharmaceutical Statistics
Volume21
Issue number6
DOIs
StatePublished - 2011

Keywords

  • Binary data
  • Closure
  • Family-wise error rate
  • Multiple tests
  • Nonnormality
  • Permutation tests
  • Simultaneous intervals

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