Enhancing Team Science by Training Collaborative Biostatisticians to have a Strong Statistical Voice

Gina Maria Pomann; Steven C. Grambow; Marissa C. Ashner; Bibhas Chakraborty; Nan Liu; Megan L. Neely; Sarah Peskoe; Lacey Rende; Emily Slade; Tracy Truong; Lexie Zidanyue Yang; Greg P. Samsa; Jesse D. Troy

doi:10.1007/s42519-025-00522-7

Enhancing Team Science by Training Collaborative Biostatisticians to have a Strong Statistical Voice

Gina Maria Pomann
, Steven C. Grambow
, Marissa C. Ashner
, Bibhas Chakraborty
, Nan Liu
, Megan L. Neely
, Sarah Peskoe
, Lacey Rende
, Emily Slade
, Tracy Truong
, Lexie Zidanyue Yang
, Greg P. Samsa
, Jesse D. Troy

Research output: Contribution to journal › Article › peer-review

Abstract

Strong statistical voice is defined as the ability to advocate and negotiate for good and ethical statistical practices, including integrating and resolving differing scientific approaches. This skill is crucial for biostatisticians who work on biomedical research teams, as it ensures the integrity and accuracy of statistical analyses and fosters productive collaborations with non-statisticians. Despite its importance, new graduates often lack targeted training opportunities. This manuscript presents a scalable training approach through the development of online videos. Preliminary didactic materials focused on two key applications: providing written comments on manuscripts and engaging in study design discussions. To evaluate this training approach, a survey was conducted among biostatistics staff in the Duke Biostatistics, Epidemiology, and Research Design Core. The survey results indicated that all respondents strongly agreed on the importance of strong statistical voice in biostatistics practice. The clarity of the training materials and examples received positive feedback, though suggestions for improvement included enhancing video engagement and providing more hands-on training. This information will guide the development of formal training videos embedded within a mentored training program that aims to teach biostatisticians and other quantitative scientists how to effectively work on teams in biomedical research.

Original language	English
Article number	13
Number of pages	28
Journal	Journal of Statistical Theory and Practice
Volume	20
Issue number	1
DOIs	https://doi.org/10.1007/s42519-025-00522-7
State	Published - Mar 2026

Bibliographical note

Publisher Copyright:
© The Author(s) 2025.

Funding

This project was supported by the NIH National Center for Advancing Translational Sciences through grant numbers UL1TR002553 (G-M.P, S.C.G., L.Z.Y., L.R.) and UL1TR001998 (E.S.) and the NIH National Institute of General Medical Science through grant number R25GM155474 (G.M.-P., S.P., L.R., E.S., T.T. G.P.S., J.D.T.). This content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This manuscript presents a framework for training biostatisticians to navigate challenging conversations with non-quantitative team members and enhance their effectiveness within biomedical research teams. The framework includes online training videos with examples and activities evaluated on a sample of its target audience: collaborative biostatisticians embedded within multidisciplinary research teams at Duke University. Survey feedback from the Duke Biostatistics, Epidemiology, and Research Design Methods Core (BERD Core) is reviewed to assist in the development of scalable training resources. The feedback will inform current training within the unit and materials developed for the Quantitative Team Science Program funded by the National Institute of General Medical Sciences (R25GM155474). The manuscript first describes the target audience, next decomposes the critical components of strong statistical voice, then outlines methods for designing materials with tangible didactic value and concludes with considerations for future modifications and national program implementation.

Funders	Funder number
National Institutes of Health (NIH)
National Institute of General Medical Sciences DP2GM119177 Sophie Dumont National Institute of General Medical Sciences	R25GM155474
National Center for Advancing Translational Sciences (NCATS)	UL1TR001998, UL1TR002553
NIH National Institute of General Medical Science	R25GM155474
NIH National Center for Advancing Translational Sciences and Center for Clinical and Translational Science	UL1TR001998, UL1TR002553

Keywords

Professional development
Statistical competencies
Strong statistical voice
Team science training
Workforce development

ASJC Scopus subject areas

Statistics and Probability

Access to Document

10.1007/s42519-025-00522-7

Cite this

Pomann, G. M., Grambow, S. C., Ashner, M. C., Chakraborty, B., Liu, N., Neely, M. L., Peskoe, S., Rende, L., Slade, E., Truong, T., Yang, L. Z., Samsa, G. P., & Troy, J. D. (2026). Enhancing Team Science by Training Collaborative Biostatisticians to have a Strong Statistical Voice. Journal of Statistical Theory and Practice, 20(1), Article 13. https://doi.org/10.1007/s42519-025-00522-7

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Enhancing Team Science by Training Collaborative Biostatisticians to have a Strong Statistical Voice

Abstract

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this