Description Usage Arguments Value References Examples

Given an ANOVA model with r levels, we are interested in testing the pairwise mean differences (1 vs 2,...; 2 vs 3,... etc). We consider a weighted multiple hypothesis testing problem, where we allow different tests to get unequal type I errors, and in the meantime, we want to control the overall type I errors (familywise error rate; FWER) at a pre-specified level. For a given comparison, we compute the multiple testing adjusted p-value, which is the smallest FWER that will lead to a significant test for the given comparison.

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`nr` |
the sample sizes for each factor level. |

`Qx` |
observed t-statistic for a comparison |

`ik` |
index of the comparison that we want to compute the multiple testing adjusted p-value |

`W` |
the relative type I errors assigned to each comparison. |

- alpha
multiple testing adjusted p-value (FWER)

- FPi
individual test type I errors

Ling,S., Johnson,C., Ellermann,J., Eberly,L. and Wu,B. (2019) A generalized Tukey method for weighted multiple pairwise comparisons in an ANOVA model.

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