Second-generation p-values: Improved rigor, reproducibility, & transparency in statistical analyses.
Second-generation p-values: Improved rigor, reproducibility, & transparency in statistical analyses.
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DOI：
10.1371/journal.pone.0188299
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发表时间：
2018
期刊：
影响因子：
3.7
通讯作者：
Greevy RA Jr
中科院分区：
文献类型：
--
作者：
Blume JD;D'Agostino McGowan L;Dupont WD;Greevy RA Jr
证明统计学上显著的结果具有科学意义不仅是良好的科学实践，而且是控制I类错误率的自然方法。在这里，我们介绍了一种新的p值扩展-第二代p值（pδ）-正式解释了科学相关性并利用了这种自然的I型错误控制。该方法依赖于一个预先指定的区间零假设，该假设代表了科学上不感兴趣或实际上为零的效应量的集合。第二代p值是数据支持的假设也是零假设的比例。因此，第二代p值表示数据何时与零假设（pδ = 1）或备择假设（pδ = 0）相容，或数据何时不确定（0 < pδ < 1）。此外，第二代p值为多重比较提供了适当的科学调整，并降低了错误发现率。这对于数据丰富的环境来说是一个进步，传统的p值调整是不必要的惩罚。第二代p值通过先验指定哪些候选假设实际上有意义，并通过提供更可靠的统计摘要来说明数据何时与替代假设或零假设兼容，从而提高了科学结果的透明度，严谨性和可重复性。
Verifying that a statistically significant result is scientifically meaningful is not only good scientific practice, it is a natural way to control the Type I error rate. Here we introduce a novel extension of the p-value—a second-generation p-value (pδ)–that formally accounts for scientific relevance and leverages this natural Type I Error control. The approach relies on a pre-specified interval null hypothesis that represents the collection of effect sizes that are scientifically uninteresting or are practically null. The second-generation p-value is the proportion of data-supported hypotheses that are also null hypotheses. As such, second-generation p-values indicate when the data are compatible with null hypotheses (pδ = 1), or with alternative hypotheses (pδ = 0), or when the data are inconclusive (0 < pδ < 1). Moreover, second-generation p-values provide a proper scientific adjustment for multiple comparisons and reduce false discovery rates. This is an advance for environments rich in data, where traditional p-value adjustments are needlessly punitive. Second-generation p-values promote transparency, rigor and reproducibility of scientific results by a priori specifying which candidate hypotheses are practically meaningful and by providing a more reliable statistical summary of when the data are compatible with alternative or null hypotheses.
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