Department of Epidemiology and Biostatistics, UT Health Science Center, San Antonio, TX 78229, USA.
Stat Med. 2011 Oct 15;30(23):2785-92. doi: 10.1002/sim.4282. Epub 2011 Jul 12.
Statistical analysis is a cornerstone of the scientific method and evidence-based medicine, and statisticians serve an increasingly important role in clinical and translational research by providing objective evidence concerning the risks and benefits of novel therapeutics. Researchers rely on statistics and informatics as never before to generate and test hypotheses and to discover patterns of disease hidden within overwhelming amounts of data. Too often, clinicians and biomedical scientists are not adequately proficient in statistics to analyze data or interpret results, and statistical expertise may not be properly incorporated within the research process. We argue for the ethical imperative of statistical standards, and we present ten nontechnical principles that form a conceptual framework for the ethical application of statistics in clinical and translational research. These principles are drawn from the literature on the ethics of data analysis and the American Statistical Association Ethical Guidelines for Statistical Practice.
统计学分析是科学方法和循证医学的基石，统计学家在临床和转化研究中通过提供有关新型治疗方法的风险和益处的客观证据，发挥着越来越重要的作用。研究人员前所未有地依赖统计学和信息学来生成和检验假设，并发现隐藏在大量数据中的疾病模式。临床医生和生物医学科学家往往不具备足够的统计学能力来分析数据或解释结果，而且统计专业知识可能没有在研究过程中得到适当的纳入。我们认为统计标准具有伦理必要性，并提出了十个非技术性原则，这些原则构成了临床和转化研究中统计伦理应用的概念框架。这些原则来自数据分析伦理文献和美国统计协会统计实践伦理准则。
