Issues with data and analyses: Errors, underlying themes, and potential solutions
Issues with data and analyses: Errors, underlying themes, and potential solutions
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DOI：
10.1073/pnas.1708279115
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发表时间：
2018-03-13
影响因子：
11.1
通讯作者：
Allison, David B.
中科院分区：
文献类型：
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作者：
Brown, Andrew W.;Kaiser, Kathryn A.;Allison, David B.
科学的某些方面，在最广泛的层面上，在实证研究中是普遍的。其中包括收集、分析和报告数据。在这些方面中的每一个方面，都可能并且确实发生错误。在这项工作中，我们首先讨论了关注统计和数据错误以不断改进科学实践的重要性。然后，我们描述了潜在的主题类型的错误和假设的影响因素。为了做到这一点，我们描述了一个案例系列的相对严重的数据和统计错误加上调查的某些类型的错误，以更好地表征的幅度，频率和趋势。在检查了这些错误之后，我们接着讨论特定错误或错误类别的后果。最后，鉴于提取的主题，我们讨论了方法，文化和系统级的方法，以减少常见的错误的频率。这些方法将有助于自我批判，自我纠正，不断发展的科学实践，并最终促进知识。
Some aspects of science, taken at the broadest level, are universal in empirical research. These include collecting, analyzing, and reporting data. In each of these aspects, errors can and do occur. In this work, we first discuss the importance of focusing on statistical and data errors to continually improve the practice of science. We then describe underlying themes of the types of errors and postulate contributing factors. To do so, we describe a case series of relatively severe data and statistical errors coupled with surveys of some types of errors to better characterize the magnitude, frequency, and trends. Having examined these errors, we then discuss the consequences of specific errors or classes of errors. Finally, given the extracted themes, we discuss methodological, cultural, and system-level approaches to reducing the frequency of commonly observed errors. These approaches will plausibly contribute to the self-critical, self-correcting, ever-evolving practice of science, and ultimately to furthering knowledge.