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零假设显著性检验与p值的二分法:人皆会犯错。

The null hypothesis significance test and the dichotomization of the p-value: Errare Humanum Est.

作者信息

Mezones-Holguín Edward, Al-Kassab-Córdova Ali, Soto-Becerra Percy, Hernández-Díaz Sonia, Kaufman Jay S

机构信息

Centro de Excelencia en Investigaciones Económicas y Sociales en Salud, Universidad San Ignacio de Loyola, Lima, Perú.

Vicerrectorado de Investigación, Universidad Continental, Huancayo, Perú.

出版信息

Rev Peru Med Exp Salud Publica. 2025 Jan 31;41(4):422-430. doi: 10.17843/rpmesp.2024.414.14285..

Abstract

Decision-making in healthcare is complex and needs to be based on the best scientific evidence. In this process, information derived from statistical analysis of data is crucial, which can be developed from either frequentist or Bayesian perspectives. When it comes to the frequentist field, the null hypothesis significance test (NHST) and its p-value is one of the most widely used techniques in different disciplines. However, NHST has been subjected to questioning from different academic points of view, which has led to it being considered as one of the causes of the so-called replicability crisis in science. In this review article, we provide a brief historical account of its development, summarize the underlying methods, describe some controversies and limitations, address misuse and misinterpretation, and finally give some scopes and reflections in the context of biomedical research.

摘要

医疗保健中的决策十分复杂,需要基于最佳科学证据。在此过程中,从数据统计分析得出的信息至关重要,这可以从频率学派或贝叶斯学派的角度来展开。在频率学派领域,零假设显著性检验(NHST)及其p值是不同学科中使用最广泛的技术之一。然而,NHST受到了来自不同学术观点的质疑,这导致它被视为科学中所谓可重复性危机的原因之一。在这篇综述文章中,我们简要介绍了其发展的历史,总结了基本方法,描述了一些争议和局限性,探讨了误用和错误解读的情况,最后在生物医学研究的背景下给出了一些范围和思考。

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