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    Statistical competencies for medical research learners: What is fundamental?

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    Date
    2017-06
    Authors
    Benn, EKT
    Carter, RE
    Enders, FT
    Grambow, Steven C
    Kidwell, KM
    Larson, J
    Lindsell, Christopher J
    Mayo, MS
    Oster, RA
    Perkins, SM
    Pollock, BH
    Rahbar, MH
    Spratt, H
    Thurston, SW
    Welty, LJ
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    (15 total)
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    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.
    Type
    Journal article
    Subject
    Clinical and Translational Science
    Evidence-Based Medicine
    Public Health
    Statistical competency
    team science
    Permalink
    https://hdl.handle.net/10161/15968
    Published Version (Please cite this version)
    10.1017/cts.2016.31
    Publication Info
    Benn, EKT; Carter, RE; Enders, FT; Grambow, Steven C; Kidwell, KM; Larson, J; ... Welty, LJ (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.
    This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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    Scholars@Duke

    Grambow

    Steven C. Grambow

    Assistant Professor of Biostatistics and Bioinformatics
    I am a collaborative statistical scientist with experience spanning a broad range of clinical research areas, including amyotrophic lateral sclerosis (ALS), post-traumatic stress disorder (PTSD), Prader-Willi syndrome (PWS), prostate cancer, quality of colorectal cancer care, osteoarthritis, lifestyle modification through weight loss, CVD risk reduction through hypertension control, smoking cessation, and substance abuse recovery. I have experience designing and analyzing observational studie
    Open Access

    Articles written by Duke faculty are made available through the campus open access policy. For more information see: Duke Open Access Policy

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