Abstract
DUNNETT (1955) developed a procedure simultaneously comparing k treatments to one control with an exact overall type I error of α when all sampling distributions are normal. Sometimes it is desirable to compare k treatments to m≧2 controls, in particular to two controls. For instance, several new therapies (e.g., pain relievers) could be compared to two standard therapies (e.g., Aspirin and Tylenol). Alternatively, a standard therapy could be very expensive, difficult to apply and/or have bad side effects, making it useful to compare each new therapy to both standard therapy and no therapy (Placebo). Dunnett's method is expanded here to give comparisons of mean values for k treatments to mean values for m≧2 controls at an exact overall type I error of α when all sampling distributions are normal. Tabled values needed to make exact simultaneous comparisons at α = .05 are given for m = 2. An application is made to an example from the literature.
| Original language | American English |
|---|---|
| Pages (from-to) | 913-921 |
| Number of pages | 9 |
| Journal | Biometrical Journal |
| Volume | 33 |
| Issue number | 8 |
| DOIs | |
| State | Published - 1991 |
| Externally published | Yes |
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
Keywords
- Dunnett's procedure
- Multiple controls
- Multiple treatments
- Simultaneous inference