Statistical competencies for medical research learners: What is fundamental?
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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.
SubjectClinical and Translational Science
Published Version (Please cite this version)10.1017/cts.2016.31
Publication InfoBenn, 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.
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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