Optimal asymmetric one-sided group sequential tests
Optimal asymmetric one-sided group sequential tests
复制标题
DOI：
10.1093/biomet/89.1.49
复制
发表时间：
2002-03-01
期刊：
影响因子：
2.7
通讯作者：
Jennison, C
中科院分区：
文献类型：
--
作者：
Barber, S;Jennison, C
我们将 Eales & Jennison (1992) 的最优对称组序贯检验扩展到更广泛的非对称设计类别。考虑了两种形式的不对称，包括不相等的 I 型和 II 型错误率以及对原假设和替代假设的预期样本量的不同侧重点。我们讨论了最优设计的属性，并使用它们来评估 Pampallona 和 Tsiatis (1994) 提出的测试系列以及通过错误支出函数定义的两个单边测试系列的效率。我们表明，错误支出设计是非常高效的，而易于实施的 Pampallona 和 Tsiatis 测试的效率稍低，但仍离最佳状态不远。我们的结果表明，不对称设计可以减少一种假设下的预期样本量，但代价是在另一种假设下明显更大的预期样本量。
We extend the optimal symmetric group sequential tests of Eales & Jennison (1992) to the broader class of asymmetric designs. Two forms of asymmetry are considered, involving unequal type I and type II error rates and different emphases on expected sample sizes at the null and alternative hypotheses. We discuss the properties of our optimal designs and use them to assess the efficiency of the family of tests proposed by Pampallona & Tsiatis (1994) and two families of one-sided tests defined through error spending functions. We show that the error spending designs are highly efficient, while the easily implemented tests of Pampallona & Tsiatis are a little less efficient but still not far from optimal. Our results demonstrate that asymmetric designs can decrease the expected sample size under one hypothesis, but only at the expense of a significantly larger expected sample size under the other hypothesis.