Hochheimer Camille J, Bosma Grace N, Gunn-Sandell Lauren, Sammel Mary D
Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, USA.
Stat. 2024;13(1). doi: 10.1002/sta4.653. Epub 2024 Feb 11.
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.
随着数据和代码共享政策越来越普遍，版本控制在统计学中得到更广泛的应用，可重复性研究的标准比以往任何时候都更高。可重复性研究实践必须跟上研究的快速步伐。为此，我们建议将现代领导实践与协作统计中可重复性研究的最佳实践相结合，作为一种有效工具，在确保质量和准确性的同时，培养我们所领导人员的管理能力和自主性。首先，我们建立一个可重复性统计研究的期望框架。然后，我们介绍斯蒂芬·M·R·柯维的信任和激励型领导理论。当我们展示管理协议如何用于使可重复性编码成为团队规范时，这两者结合在一起。我们提供一个说明性的代码示例，并强调这种方法如何创造一种更具协作性而非评价性的文化，在这种文化中团队成员对自己负责。本文的目的是让统计学家发现这种领导理论的应用有用，并激励他们有意发展自己的个人领导方式。
