Teaching Short Courses in Biostatistics and Epidemiology

This article summarizes the author's personal history and experience with teaching short courses. Topics discussed include the rationale for the existence of short courses, the organization and various components of short courses, and some issues and problems to be considered for a short course to be successful.     

Biostatistics and epidemiology

The fields of biostatistics and epidemiology are described. Their relationship to each other and recent advances are emphasized.     

生物统计的研究进展与挑战

生物统计学是以解决生物学、医学、公共卫生学、农学等领域科学问题为目标的应用型学科,近年来在精准医疗的背景下得以快速发展.另一方面,生物统计研究面对的数据存在海量化、复杂化和异质化的大数据特征,对理论与应用研究者都提出了新的挑战.本文围绕生物统计研究中的流行病学研究、临床试验设计、生存数据分析和基因数据分析展开讨论,在介绍基本思路的基础上对最新挑战及前沿发展方向进行展望.     

Biostatistics:a difficult road ahead

We are now well into the nineteen-eighties and looking back over the last ten years one of the most striking, perhaps the most striking, aspect of biostatistics and statistical epidemiology is sheer volume of literature that has emerged. Any historian of our subject is bound to ask two major and not unrelated questions! how much of this was necessary and how much of it was of direct use to clinical science in the sense of giving real aid to progress in medicine?.     

Biostatistics Instruction at Meharry Medical College

In a variety of settings, it is desirable to display a collection of likelihoods over a common interval. One approach is simply to superimpose the likelihood curves. However, where there are more than a handful of curves, such displays are extremely difficult to decipher. An alternative is simply to display a point estimate with a confidence interval, corresponding to each likelihood. However, these may be inadequate when the likelihood is not approximately normal, as can occur with small sample sizes or nonlinear models. A second dimension is needed to gauge the relative plausibility of different parameter values. We introduce the raindrop plot, a shaded figure over the range of parameter values having log-likelihood greater than some cutoff, with height varying proportional to the difference between the log-likelihood and the cutoff. In the case of a normal likelihood, this produces a reflected parabola so that deviations from normality can be easily detected. An analogue of the raindrop plot can also be used to display estimated random effect distributions, posterior distributions, and predictive distributions.     

Biostatistics Faculty and NIH Awards at U.S. Medical Schools

Statistical principles and methods are critical to the success of biomedical and translational research. However, it is difficult to track and evaluate the monetary value of a biostatistician to a medical school (SoM). Limited published data on this topic are available, especially comparing across SoMs. Using National Institutes of Health (NIH) awards and American Association of Medical Colleges (AAMC) faculty counts data (2010–2013), together with online information on biostatistics faculty from 119 institutions across the country, we demonstrated that the number of biostatistics faculty was significantly positively associated with the amount of NIH awards, both as a school total and on a per faculty basis, across various sizes of U.S. SoMs. Biostatisticians, as a profession, should be proactive in communicating and advocating the value of their work and their unique contribution to the long-term success of a biomedical research enterprise. Supplementary materials for this article are available online.     

Analogies for Helping Clinicians and Investigators Better Understand the Principles and Practice of Biostatistics

For the interaction between the biostatistician and the clinician or research investigator to be successful, it is important not only for the investigator to be able to explain biological and medical principles in a way that can be understood by the biostatistician, so, too, the biostatistician needs tools to help the investigator understand both the practice of statistics and specific statistical methods. In our practice, we have found it useful to draw analogies between statistical concepts and familiar medical or everyday ideas. These analogies help to stress a point or provide an understanding on the part of the investigator. For example, explaining the reason for using a nonparametric procedure (a general procedure used when the underlying distribution of the data is not known or cannot be assumed) by comparing it to using broad spectrum antibiotics (a general antibiotic used when the specific bacteria causing infection is unknown or cannot be assumed) can be an effective teaching tool. We present a variety of useful (and hopefully amusing) analogies that can be adopted by statisticians to help investigators at all levels of experience better understand principles and practice of statistics.     

Strategies for Success: Early-Stage Collaborating Biostatistics Faculty in an Academic Health Center

Collaborative biostatistics faculty (CBF) are increasingly valued by academic health centers (AHCs) for their role in increasing success rates of grants and publications, and educating medical students and clinical researchers. Some AHCs have a biostatistics department that consists of only biostatisticians focused on methodological research, collaborative research, and education. Others may have a biostatistics unit within an interdisciplinary department, or statisticians recruited into clinical departments. Within each model, there is also variability in environment, influenced by the chair's background, research focus of colleagues, type of students taught, funding sources, and whether the department is in a medical school or school of public health. CBF appointments may be tenure track or nontenure, and expectations for promotion may vary greatly depending on the type of department, track, and the AHC. In this article, the authors identify strategies for developing early-stage CBFs in four domains: (1) Influence of department/environment, (2) Skills to develop, (3) Ways to increase productivity, and (4) Ways to document accomplishments. Graduating students and postdoctoral fellows should consider the first domain when choosing a faculty position. Early-stage CBFs will benefit by understanding the requirements of their environment early in their appointment and by modifying the provided progression grid with their chair and mentoring team as needed. Following this personalized grid will increase the chances of a satisfying career with appropriate recognition for academic accomplishments.