Simultaneous Comparisons of Multiple Treatments to Two (or More) Controls

Abstract

Dunnett (1955) developed a procedure comparing m treatments to one control with an exact overall type I error of alpha when all sampling distributions as normal. Sometimes it is desirable to compare m treatments to K > or = 2 controls. In particular, it is often desired to compare m treatments with two controls. For instance, several new treatments (e.g., pain relievers) could be compared to two standard treatments (e.g., Aspirin and Tylenol). Alternatively, a standard treatment could be very expensive, difficult to apply and/or have bad side effects, making it useful to compare each new treatment to both standard treatment and not treatment (Placebo). Dunnett's method is expanded here to give comparisons of mean values for m treatments to mean values for K > or = 2 controls at an exact overall type I error of a alpha when all sampling distributions are normal. Tabled values needed to make exact simultaneous comparisons at alpha =.05 are given for K=2. An application is made to an illustrative example for the literature.

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Document Details

Document Type
Technical Report
Publication Date
Dec 27, 1990
Accession Number
ADA231079

Entities

People

  • Donald R. Hoover

Organizations

  • Stanford University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • California
  • Computers
  • Confidence Limits
  • Data Science
  • Errors
  • Information Science
  • Intervals
  • Mainframe Computers
  • Order Statistics
  • Plastic Explosives
  • Probability
  • Sampling
  • Side Effects
  • Statistics
  • Symmetry
  • Two Dimensional
  • United States

Fields of Study

  • Mathematics

Readers

  • Neurotrauma and Rehabilitation Medicine.
  • Regression Analysis.