### Abstract

For i = 1,..., p, let X_{i1},..., X_{ini} denote independent random samples from normal populations. The ith population has unknown mean μ_{i} and unknown variance σ_{i}^{2}. We consider the sign testing problem of testing H_{0}: μ_{i} ≤ a_{i}, for some i=1,..., p, versus H_{1}: μ_{i} > a_{i}, for all i=1,..., p, where a_{1},..., a_{p} are fixed constants. Here, H_{1} might represent p different standards that a product must meet before it is considered acceptable. For 0 < α < 1/2, we first derive the size-α likelihood ratio test (LRT) for this problem, and then we describe an intersection-union test (IUT) that is uniformly more powerful than the likelihood ratio test if the sample sizes are not all equal. For a more general model than the normal, we describe two intersection-union tests that maximize the size of the rejection region formed by intersection. Applying these tests to the normal problem yields two tests that are uniformly more powerful than both the LRT and IUT described above. A small power comparison of these tests is given.

Original language | English (US) |
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Pages (from-to) | 187-205 |

Number of pages | 19 |

Journal | Journal of Statistical Planning and Inference |

Volume | 107 |

Issue number | 1-2 |

DOIs | |

State | Published - Sep 1 2002 |

### Keywords

- Independence
- Intersection-union test
- Likelihood ratio test
- Min test
- Normal population
- t distribution

### ASJC Scopus subject areas

- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics

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## Cite this

*Journal of Statistical Planning and Inference*,

*107*(1-2), 187-205. https://doi.org/10.1016/S0378-3758(02)00252-5