Reproducible research practices: A tool for effective and efficient leadership in collaborative statistics

Pub Date : 2024-02-11 DOI:10.1002/sta4.653
Camille J. Hochheimer, Grace N. Bosma, Lauren Gunn-Sandell, Mary D. Sammel
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Abstract

With data and code sharing policies more common and version control more widely used in statistics, standards for reproducible research are higher than ever. Reproducible research practices must keep up with the fast pace of research. To do so, we propose combining modern practices of leadership with best practices for reproducible research in collaborative statistics as an effective tool for ensuring quality and accuracy while developing stewardship and autonomy in the people we lead. First, we establish a framework for expectations of reproducible statistical research. Then, we introduce Stephen M.R. Covey's theory of trusting and inspiring leadership. These two are combined as we show how stewardship agreements can be used to make reproducible coding a team norm. We provide an illustrative code example and highlight how this method creates a more collaborative rather than evaluative culture where team members hold themselves accountable. The goal of this manuscript is for statisticians to find this application of leadership theory useful and to inspire them to intentionally develop their personal approach to leadership.
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可复制的研究实践:切实有效领导合作统计工作的工具
随着数据和代码共享政策越来越普遍,版本控制在统计领域的应用也越来越广泛,可重复研究的标准比以往任何时候都要高。可重复研究实践必须跟上快速的研究步伐。为此,我们建议将现代领导力实践与合作统计中的可重现研究最佳实践相结合,作为确保质量和准确性的有效工具,同时培养我们所领导的人员的管理能力和自主性。首先,我们建立了一个对可重复统计研究的期望框架。然后,我们介绍斯蒂芬-柯维(Stephen M.R. Covey)的信任和激励型领导理论。我们将这两者结合起来,展示如何利用管理协议使可重复编码成为团队规范。我们提供了一个代码示例,并强调了这种方法如何创造出一种更具协作性而非评价性的文化,让团队成员对自己负责。本手稿的目的是让统计人员发现领导力理论的应用非常有用,并激励他们有意识地发展个人的领导力方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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