Description Usage Arguments Value Author(s) References Examples

The function applies to testing problem with either t distributed test statistics or (approximately) normally distributed test statistics. The function accomodates both equally correlated and unequally correlated test statistics.

1 |

`k` |
Number of hypotheses to be tested, |

`alpha` |
The pre-specified overall significance level, default=0.05. |

`alternative` |
The alternative hypothesis: "U"=upper one-sided test (default); "B"=two-sided test. For lower one-sided tail test, specify alternative="U" and use the negations of the return critical constants. |

`df` |
Degree of freedom of the t-test statistics. When (approximately) normally distributed test statistics are applied, set df=Inf (default). |

`corr` |
Specified for equally correlated test statistics, which is the common correlation between the test statistics, default=0.5. |

`corr.matrix` |
Specified for unequally correlated test statistics, which is the correlation matrix of the test statistics, default=NA. |

Return a k-vector of critical constants from smallest to largest.

FAN XIA <phoebexia@yahoo.com>

Charles W Dunnett and Ajit C Tamhane. Step-down multiple tests for comparing treatments with a control in unbalanced one-way layouts. Statistics in Medicine, 10(6):939-947, 1991.

1 2 3 4 5 6 7 8 | ```
#To test four hypotheses, the test statistics are
#2.2 (H1), 2.7 (H2), 2.1(H3), 0.85(H4), respectively.
#The test statistcis are equally correlated at 0.6 and have df=30.
#At overall one-sided significance level 0.05, the critical constants are given by:
cvSDDT(k=4,df=30,corr=0.6)
#based on the critical values, we reject H2, H1, H3 in a sequence and accept H4.
``` |

```
Loading required package: mvtnorm
c1 c2 c3 c4
1.697 1.970 2.118 2.217
```

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