A reproducible analysis is one in which an independent entity, using the same data and the same statistical code, would obtain the exact same result as the previous analyst. Reproducible analyses utilize script-based analyses and open data to aid in the reproduction of the analysis. A reproducible analysis does not ensure the same results are obtained if another sample of data is obtained, often referred to as replicability. Reproduction and replication of studies are discussed as well as the overwhelming benefits of creating a reproducible analysis workflow. A tool is proposed to aid in the evaluation of studies to describe which element in a study has a strong reproducible workflow and areas that could be improved. This tool is meant to serve as a discussion tool, not to rank studies or devalue studies that are unable to share data or statistical code. Finally, discussion surrounding reproducibility for qualitative studies are discussed along with unique challenges for adopting a reproducible analysis framework.

可重现的分析是指一个独立的实体，使用相同的数据和相同的统计代码，将获得与之前的分析师完全相同的结果。可重现的分析利用基于脚本的分析和开放数据来帮助分析的再现。如果获得另一个数据样本（通常称为可复制性），则可重现的分析不能确保获得相同的结果。讨论了研究的复制和复制，以及创建可重现的分析工作流程的压倒性优势。提出了一种工具来帮助评估研究，以描述研究中哪个要素具有可重现的强大工作流程以及可以改进的领域。该工具旨在用作讨论工具，不能对无法共享数据或统计代码的研究进行排名或贬值研究。最后，围绕定性研究的可再现性的讨论，以及采用可再现分析框架所面临的独特挑战。