《禅与多重比较的艺术》
Zen and the art of multiple comparisons.
作者信息
Lindquist Martin A, Mejia Amanda
机构信息
From the Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland.
出版信息
Psychosom Med. 2015 Feb-Mar;77(2):114-25. doi: 10.1097/PSY.0000000000000148.
OBJECTIVE
The need for appropriate multiple comparisons correction when performing statistical inference is not a new problem. However, it has come to the forefront in many new modern data-intensive disciplines. For example, researchers in areas such as imaging and genetics are routinely required to simultaneously perform thousands of statistical tests. Ignoring this multiplicity can cause severe problems with false positives, thereby introducing nonreproducible results into the literature.
METHODS
This article serves as an introduction to hypothesis testing and multiple comparisons for practical research applications, with a particular focus on its use in the analysis of functional magnetic resonance imaging data.
RESULTS
We discuss hypothesis testing and a variety of principled techniques for correcting for multiple tests. We also illustrate potential pitfalls problems that can occur if the multiple comparisons issue is not dealt with properly. We conclude, by discussing effect size estimation, an issue often linked with the multiple comparisons problem.
CONCLUSIONS
Failure to properly account for multiple comparisons will ultimately lead to heightened risks for false positives and erroneous conclusions.
目的
在进行统计推断时，需要进行适当的多重比较校正并非一个新问题。然而，它在许多新的现代数据密集型学科中已成为前沿问题。例如，成像和遗传学等领域的研究人员经常需要同时进行数千次统计检验。忽略这种多重性会导致严重的假阳性问题，从而将不可重复的结果引入文献中。
方法
本文作为假设检验和多重比较在实际研究应用中的介绍，特别关注其在功能磁共振成像数据分析中的应用。
结果
我们讨论假设检验以及多种用于校正多重检验的原则性技术。我们还说明了如果多重比较问题处理不当可能出现的潜在陷阱问题。通过讨论效应量估计，我们得出结论，效应量估计是一个经常与多重比较问题相关联的问题。
结论
未能正确考虑多重比较最终将导致假阳性和错误结论的风险增加。
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