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| Titel: |
Selecting all treatments better than a control with a binomial prior distribution |
| Auteur: |
Chen, Hubert J. Chen, Shun-Yi Sirichote, Jirawan |
| Verschenen in: |
Communications in statistics |
| Paginering: | Jaargang 14 (1985) nr. 1 pagina's 187-221 |
| Jaar: |
1985 |
| Inhoud: |
Let π1,…,πk denote k treatment populations and let πk represent thex control population. It is assumed that data obtained from (π0, π1,…,πk) by a repeated measurements design follow a multivariate normal distribution with mean vector (π0, π1,…, πk) and covariance matrix £0. Then, if “better” is defined to mean “at least as good as” (πi > π0) we propose selection procedures for selecting a subset which includes all treatments better than the control. Due to the fact that the number of better populations is unknown, a binomial prior distribution on this unknown factor is assumed. Consequently, the exact infimum of probability of correct selection is obtained. Statistical tables to implement these procedure are extensively constructed and expected subset size is also considered. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 18 van 19 gevonden artikelen
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