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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.
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.’
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%).
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.
This chapter highlights some important aspects of the design and analysis of clinical trials, and sketches a number of relevant statistical concepts. A controlled clinical trial of a medical intervention should have at least one primary hypothesis that drives its design. Well-designed and well-executed trials include an unambiguous protocol approved by the Institutional Review Boards (IRBs) or Ethics Committees of the participating clinics, laboratories, and data centers. The chapter also describes the basic frequentist statistical testing paradigm used by the typical randomized clinical trial with particular reference to ideas necessary in selecting sample size. Most clinical trials study more than one outcome of interest. Many neurological clinical trials compare therapies with respect to time to occurrence of the primary outcome. In the past, few clinical trials were performed in the Bayesian framework, but Bayesian methods have become more widely used recently.