The Science of Statistical Practice

Emerging technologies, such as artificial intelligence, emphasize the importance of quantitative methods and their applications when conducting increasingly data-intensive research. The scientific discipline of statistical practice is critical for achieving rigor in research addressing important domain-level questions. The misconception that statistical practice is not a science but rather a service threatens scientific rigor and compromises the quality of its contribution to clinical and translational research. The authors call on academic and research leadership to recognize statistical practice as a key scientific discipline and to further ensure that the field and its scientists are nurtured. To that end, academic homes for faculty of statistical practice and its scholarship need to be fostered with clear pathways to hire, retain, promote, and tenure faculty who are largely team scientists. This goal can be achieved inclusively by avoiding the creation of separate faculty lines that might imply differing levels of value. In contrast, we must recognize and appreciate equally significant intellectual contributions made by various types of faculty members. Additionally, engagement of statistical practitioners as peer scientists and coleaders in collaborative research will ensure higher quality and rigor of scientific endeavors. Finally, leaders of statistical practice must be included in critical discussions around strategic development for academic and other research organizations for those institutions to achieve their missions in this modern era of data-intensive research.