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P in the right place: Revisiting the evidential value of P‐values

机译:P在正确的位置:重新探究P值的证据价值

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摘要

P‐values are often calculated when testing hypotheses in quantitative settings, and low P‐values are typically used as evidential measures to support research findings in published medical research. This article reviews old and new arguments questioning the evidential value of P‐values. Critiques of the P‐value include that it is confounded, fickle, and overestimates the evidence against the null. P‐values may turn out falsely low in studies due to random or systematic errors. Even correctly low P‐values do not logically provide support to any hypothesis. Recent studies show low replication rates of significant findings, questioning the dependability of published low P‐values. P‐values are poor indicators in support of scientific propositions. P‐values must be inferred by a thorough understanding of the study's question, design, and conduct. Null hypothesis significance testing will likely remain an important method in quantitative analysis but may be complemented with other statistical techniques that more straightforwardly address the size and precision of an effect or the plausibility that a hypothesis is true.
机译:在定量设置中检验假设时,通常会计算P值,而低P值通常用作支持已发表医学研究结果的证据。本文回顾了质疑P值的证据价值的新旧论点。对P值的批评包括它是混杂的,善变的,并且高估了针对零值的证据。由于随机或系统错误,P值可能会在研究中错误地降低。即使正确的低P值在逻辑上也无法为任何假设提供支持。最近的研究表明,重要发现的重复率很低,这对已发表的低P值的可靠性提出了质疑。 P值是支持科学命题的不良指标。必须通过对研究的问题,设计和行为的透彻理解来推断P值。无效假设重要性检验可能仍将是定量分析中的一种重要方法,但可能会与其他统计技术相辅相成,这些统计技术可以更直接地解决效应的大小和精度或假设成立的真实性。

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