Principles for the ethical analysis of clinical and translational research

Jonathan A.L. Gelfond, Elizabeth Heitman, Brad H. Pollock, Craig M. Klugman

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)2785-2792
Number of pages8
JournalStatistics in Medicine
Issue number23
StatePublished - Oct 15 2011


  • Data analysis
  • Ethics
  • Translational research

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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