Statistical competencies for medical research learners: What is fundamental?

Abstract

INTRODUCTION: It is increasingly essential for medical researchers to be literate in statistics, but the requisite degree of literacy is not the same for every statistical competency in translational research. Statistical competency can range from 'fundamental' (necessary for all) to 'specialized' (necessary for only some). In this study, we determine the degree to which each competency is fundamental or specialized. METHODS: We surveyed members of 4 professional organizations, targeting doctorally trained biostatisticians and epidemiologists who taught statistics to medical research learners in the past 5 years. Respondents rated 24 educational competencies on a 5-point Likert scale anchored by 'fundamental' and 'specialized.' RESULTS: There were 112 responses. Nineteen of 24 competencies were fundamental. The competencies considered most fundamental were assessing sources of bias and variation (95%), recognizing one's own limits with regard to statistics (93%), identifying the strengths, and limitations of study designs (93%). The least endorsed items were meta-analysis (34%) and stopping rules (18%). CONCLUSION: We have identified the statistical competencies needed by all medical researchers. These competencies should be considered when designing statistical curricula for medical researchers and should inform which topics are taught in graduate programs and evidence-based medicine courses where learners need to read and understand the medical research literature.

Department

Description

Provenance

Subjects

Clinical and Translational Science, Evidence-Based Medicine, Public Health, Statistical competency, team science

Citation

Published Version (Please cite this version)

10.1017/cts.2016.31

Publication Info

Enders, Felicity T, Christopher J Lindsell, Leah J Welty, Emma KT Benn, Susan M Perkins, Matthew S Mayo, Mohammad H Rahbar, Kelley M Kidwell, et al. (2017). Statistical competencies for medical research learners: What is fundamental?. J Clin Transl Sci, 1(3). pp. 146–152. 10.1017/cts.2016.31 Retrieved from https://hdl.handle.net/10161/15968.

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Scholars@Duke

Grambow

Steven C. Grambow

Associate Professor of Biostatistics & Bioinformatics

Transforming research education through innovation, mentorship, and collaboration.

Steven C. Grambow, PhD is Associate Professor and Associate Chair of Education in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine. He serves as Director of the Clinical Research Training Program (CRTP), Duke’s flagship degree-granting program for clinical and translational research education, and as Co-Director of the Workforce Development Pillar of the Duke Clinical and Translational Science Institute (CTSI). Dr. Grambow provides strategic oversight for multiple educational and workforce development initiatives that span the full continuum of learners, from students to faculty.

With over two decades of experience in graduate and professional education, Dr. Grambow has taught statistical methods and research design to more than 1,000 physician-scientists, clinical fellows, and faculty at Duke and the NIH. He has led the CRTP’s core statistics course for over 21 years and has directed or co-directed national and international certificate programs across multiple institutions. His expertise spans classroom, hybrid, and online environments, and he has served as a leader in designing programs that respond to evolving workforce and research needs.

A central focus of Dr. Grambow’s work is building pathways into clinical and translational research careers. He has cultivated longstanding partnerships with academic and community institutions, including North Carolina Central University and Durham Technical Community College, to create educational models that prepare learners for impactful roles in research. His efforts emphasize strong mentorship, practical experience, and tailored program design to meet learners where they are and help them advance.

Dr. Grambow is also at the forefront of educational innovation, leading initiatives that explore the integration of artificial intelligence into biostatistical training and academic workflows. His current work includes faculty development in AI literacy, emerging pedagogical models that support active learning and reflective practice, and new frameworks for clinical research education that emphasize adaptability and cross-disciplinary collaboration.

As a collaborative statistical scientist, Dr. Grambow has contributed to a wide range of clinical research studies, including observational studies, randomized trials, and epidemiologic investigations. His research collaborations have addressed public health and clinical challenges such as amyotrophic lateral sclerosis (ALS), post-traumatic stress disorder (PTSD), Prader-Willi syndrome (PWS), prostate cancer, cardiovascular risk reduction, and substance use recovery.

Dr. Grambow’s leadership has been recognized through institutional and national awards, including teaching honors from the American Statistical Association and Duke University. He brings a unique combination of academic rigor, educational strategy, and programmatic leadership to his roles, helping to shape the future of clinical research training through thoughtful innovation and sustained collaboration.


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