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Enders FT, Lindsell CJ, Welty LJ, et al. Statistical competencies for medical research learners: What is fundamental?. J Clin Transl Sci. 2017;1(3):146-152doi: 10.1017/cts.2016.31.
Enders, F. T., Lindsell, C. J., Welty, L. J., Benn, E. K. T., Perkins, S. M., Mayo, M. S., Rahbar, M. H., Kidwell, K. M., Thurston, S. W., Spratt, H., Grambow, S. C., Larson, J., Carter, R. E., Pollock, B. H., & Oster, R. A. (2017). Statistical competencies for medical research learners: What is fundamental?. Journal of clinical and translational science, 1(3), 146-152. https://doi.org/10.1017/cts.2016.31
Enders, Felicity T, et al. "Statistical competencies for medical research learners: What is fundamental?." Journal of clinical and translational science vol. 1,3 (2017): 146-152. doi: https://doi.org/10.1017/cts.2016.31
Enders FT, Lindsell CJ, Welty LJ, Benn EKT, Perkins SM, Mayo MS, Rahbar MH, Kidwell KM, Thurston SW, Spratt H, Grambow SC, Larson J, Carter RE, Pollock BH, Oster RA. Statistical competencies for medical research learners: What is fundamental?. J Clin Transl Sci. 2017 Jun;1(3):146-152. doi: 10.1017/cts.2016.31. Epub 2017 May 09. PMID: 29082029; PMCID: PMC5647667.
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J Clin Transl Sci. 2017 Jun;1(3):146-152. doi: 10.1017/cts.2016.31. Epub 2017 May 09.

Statistical competencies for medical research learners: What is fundamental?.

Journal of clinical and translational science

Felicity T Enders, Christopher J Lindsell, Leah J Welty, Emma K T Benn, Susan M Perkins, Matthew S Mayo, Mohammad H Rahbar, Kelley M Kidwell, Sally W Thurston, Heidi Spratt, Steven C Grambow, Joseph Larson, Rickey E Carter, Brad H Pollock, Robert A Oster

Affiliations

  1. Division of Biomedical Statistics & Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
  2. Department of Emergency Medicine and Center for Clinical and Translational Science and Training, University of Cincinnati, Cincinnati, OH, USA.
  3. Department of Preventive Medicine, Northwestern University, Evanston, IL, USA.
  4. Department of Population Health Science and Policy, Center for Biostatistics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  5. Department of Biostatistics, School of Medicine, Indiana University, Indianapolis, IN, USA.
  6. Department of Biostatistics, School of Medicine, University of Kansas Medical Center, Kansas City, KS, USA.
  7. Department of Internal Medicine, McGovern Medical School, Division of Clinical and Translational Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA.
  8. Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  9. Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA.
  10. Department of Preventive Medicine and Community Health, The University of Texas Medical Branch, Galveston, TX, USA.
  11. Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
  12. Department of Public Health Sciences, University of California, Davis, Davis, CA, USA.
  13. Department of Medicine, Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.

PMID: 29082029 PMCID: PMC5647667 DOI: 10.1017/cts.2016.31

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.

Keywords: Clinical and Translational Science; Evidence-Based Medicine; Public Health; Statistical competency; team science

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