Statistical methodology plays a crucial role in drug regulation. Decisions by the US Food and Drug Administration or European Medicines Agency are typically made based on multiple primary studies testing the same medical product, where the two‐trials rule is the standard requirement, despite shortcomings. A new approach is proposed for this task based on the harmonic mean of the squared study‐specific test statistics. Appropriate scaling ensures that, for any number of independent studies, the null distribution is a χ²‐distribution with 1 degree of freedom. This gives rise to a new method for combining one‐sided p‐values and calculating confidence intervals for the overall treatment effect. Further properties are discussed and a comparison with the two‐trials rule is made, as well as with alternative research synthesis methods. An attractive feature of the new approach is that a claim of success requires each study to be convincing on its own to a certain degree depending on the overall level of significance and the number of studies. The new approach is motivated by and applied to data from five clinical trials investigating the effect of carvedilol for the treatment of patients with moderate to severe heart failure.

中文翻译：

---

谐波平均值χ2检验可证实科学发现

统计方法在药物监管中起着至关重要的作用。美国食品药品监督管理局（FDA）或欧洲药品管理局（European Medicines Agency）的决定通常是基于对同一医疗产品进行测试的多项基础研究得出的，尽管有缺点，但两项试验规则是标准要求。为此，提出了一种新方法，该方法基于特定研究的统计检验平方的谐波均值。适当的缩放可确保的是，对于任何数量的独立的研究的情况下，无效分布是χ ² -配送与1个自由度。这就产生了一种新的方法来组合单边p值并计算总体治疗效果的置信区间。讨论了其他属性，并与两次试验规则进行了比较，并与其他研究综合方法进行了比较。新方法的一个吸引人的特点是，要取得成功，就必须根据总体意义和研究数量，在一定程度上说服每项研究说服自己。该新方法的灵感来自于五个临床试验的数据，这些试验研究了卡维地洛对中度至重度心力衰竭患者的治疗作用。