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Reproducible Research: A Retrospective
Annual Review of Public Health ( IF 21.4 ) Pub Date : 2021-04-02 , DOI: 10.1146/annurev-publhealth-012420-105110
Roger D Peng 1 , Stephanie C Hicks 1
Affiliation  

Advances in computing technology have spurred two extraordinary phenomena in science: large-scale and high-throughput data collection coupled with the creation and implementation of complex statistical algorithms for data analysis. These two phenomena have brought about tremendous advances in scientific discovery but have raised two serious concerns. The complexity of modern data analyses raises questions about the reproducibility of the analyses, meaning the ability of independent analysts to recreate the results claimed by the original authors using the original data and analysis techniques. Reproducibility is typically thwarted by a lack of availability of the original data and computer code. A more general concern is the replicability of scientific findings, which concerns the frequency with which scientific claims are confirmed by completely independent investigations. Although reproducibility and replicability are related, they focus on different aspects of scientific progress. In this review, we discuss the origins of reproducible research, characterize the current status of reproducibility in public health research, and connect reproducibility to current concerns about the replicability of scientific findings. Finally, we describe a path forward for improving both the reproducibility and replicability of public health research in the future.

中文翻译:


可再现的研究:回顾性研究

计算技术的进步刺激了科学界的两个非同寻常的现象:大规模和高通量的数据收集,以及用于数据分析的复杂统计算法的创建和实现。这两种现象在科学发现方面带来了巨大的进步,但引起了两个严重的问题。现代数据分析的复杂性提出了有关分析可重复性的问题,这意味着独立分析师能够使用原始数据和分析技术来再现原始作者声称的结果。通常由于缺乏原始数据和计算机代码而阻碍了可重复性。更普遍的关注是科学发现的可复制性,这涉及通过完全独立的调查确认科学主张的频率。尽管可复制性和可复制性相关,但它们专注于科学进步的不同方面。在这篇综述中,我们讨论了可再生性研究的起源,描述了公共卫生研究中可再生性的现状,并将可再生性与当前对科学发现可复制性的关注联系起来。最后,我们描述了未来改善公共卫生研究的可重复性和可复制性的途径。表征公共卫生研究中可再现性的当前状态,并将可再现性与对科学发现可再现性的当前关注联系起来。最后,我们描述了未来改善公共卫生研究的可重复性和可复制性的途径。表征公共卫生研究中可再现性的当前状态,并将可再现性与对科学发现可再现性的当前关注联系起来。最后,我们描述了未来改善公共卫生研究的可重复性和可复制性的途径。

更新日期:2021-04-04
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