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A note on multiple testing procedures in dose finding

P Bauer1

  • 1Department of Medical Statistics, University of Vienna, Austria.

Biometrics
|October 23, 1997
PubMed
Summary
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New dose-finding methods require order assumptions for error control. Safer procedures use classical many-one comparisons, avoiding restrictions on dose-response means.

Area of Science:

  • Biostatistics
  • Pharmacometrics
  • Statistical methods

Background:

  • Multiple testing procedures are crucial for dose-finding studies.
  • Recently proposed methods by Tamhane, Hochberg, and Dunnett (1996) offer advanced statistical approaches.
  • These methods aim to control the familywise error rate (FWER) in dose-response assessments.

Purpose of the Study:

  • To evaluate the assumptions underlying recently proposed multiple test procedures for dose finding.
  • To identify conditions under which strong control of the familywise error rate is guaranteed.
  • To propose alternative, broadly applicable procedures for dose-finding analysis.

Main Methods:

  • The study analyzes the theoretical properties of multiple test procedures for dose finding.

Related Experiment Videos

  • It examines the impact of assuming order relations among treatment group means.
  • It contrasts these with procedures based on classical many-one comparisons to a zero-dose control.

    • Main Results:

    • Strong control of the familywise error rate in the cited procedures is contingent upon assuming monotonic dose-response relationships.
    • Without such order assumptions, these specific procedures may not reliably control the overall error rate.
    • Procedures utilizing many-one comparisons with the zero dose offer robust error control without requiring pre-specified order relations.

    Conclusions:

    • The reliability of certain dose-finding multiple test procedures depends on assumptions about dose-response monotonicity.
    • Researchers should exercise caution when applying these methods without order restrictions.
    • Classical many-one comparisons provide a safer, assumption-free alternative for dose-finding when order cannot be guaranteed.