Abstract
A two‐stage design is proposed to choose among several experimental treatments and a standard treatment in clinical trials. The first stage employs a selection procedure to select the best treatment, provided it is better than the standard. The second stage tests the hypothesis between the best treatment selected at the first stage (if any) and the standard treatment. All the treatments are assumed to follow normal distributions and the best treatment is the one with the largest population mean. The level and the power are defined and they are used to set up equations to solve unknown first stage sample size, second stage sample size, and procedure parameters. The optimal design is the one that gives the smallest average sample size. Numerical results are presented to illustrate the improvement of one design as compared to existing one stage design.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 29-35 |
| Number of pages | 7 |
| Journal | Biometrical Journal |
| Volume | 34 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1992 |
Keywords
- Hypothesis testing
- Least favorable configuration
- Ranking and selection
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty