标题： 部分联合检验中的可接受性 显示英文标题

标题： Admissibility in Partial Conjunction Testing

摘要： 荟萃分析结合多个研究的结果，旨在提高发现共同效应的能力。如果任何一项研究显示出强烈的显著性，则通常会拒绝无效假设。部分联合零假设只有当至少$r$个$n$个分量假设是非零的时才会被拒绝，其中$r = 1$对应于常规的荟萃分析。与荟萃分析相比，它能够鼓励跨研究的可重复发现。将其应用于不同的$r$值时的一个副产品是对$r$的置信区间，用于量化非零研究的比例。Benjamini 和 Heller（2008）通过忽略最小的$r - 1$个 p 值，并对剩余的$n - r + 1$个 p 值应用有效的荟萃分析 p 值，提供了一个有效的部分联合零假设检验。我们提供了单调检验中部分联合假设可接受组合 p 值的充分必要条件。非单调检验总是优于单调检验，但通常在实践中过于不合理而无法使用。基于这些发现，我们提出了 Benjamini 和 Heller 检验的一种广义形式，该形式允许使用各种类型的荟萃分析 p 值，并将我们的方法应用于评估新抗凝剂在中风预防的患者亚组中的可重复益处的实例研究中。 显示英文摘要

摘要： Meta-analysis combines results from multiple studies aiming to increase power in finding their common effect. It would typically reject the null hypothesis of no effect if any one of the studies shows strong significance. The partial conjunction null hypothesis is rejected only when at least $r$ of $n$ component hypotheses are non-null with $r = 1$ corresponding to a usual meta-analysis. Compared with meta-analysis, it can encourage replicable findings across studies. A by-product of it when applied to different $r$ values is a confidence interval of $r$ quantifying the proportion of non-null studies. Benjamini and Heller (2008) provided a valid test for the partial conjunction null by ignoring the $r - 1$ smallest p-values and applying a valid meta-analysis p-value to the remaining $n - r + 1$ p-values. We provide sufficient and necessary conditions of admissible combined p-value for the partial conjunction hypothesis among monotone tests. Non-monotone tests always dominate monotone tests but are usually too unreasonable to be used in practice. Based on these findings, we propose a generalized form of Benjamini and Heller's test which allows usage of various types of meta-analysis p-values, and apply our method to an example in assessing replicable benefit of new anticoagulants across subgroups of patients for stroke prevention.