Institute of Medical Biochemistry Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
Elife. 2020 May 22;9:e56626. doi: 10.7554/eLife.56626.
The pressure for every research article to tell a clear story often leads researchers in the life sciences to exclude experiments that 'did not work' when they write up their results. However, this practice can lead to reporting bias if the decisions about which experiments to exclude are taken after data have been collected and analyzed. Here we discuss how to balance clarity and thoroughness when reporting the results of research, and suggest that predefining the criteria for excluding experiments might help researchers to achieve this balance.
由于每篇研究论文都需要清晰地讲述一个故事，这一压力常常导致生命科学领域的研究人员在撰写研究结果时排除那些“无效”的实验。然而，如果排除实验的决策是在数据收集和分析之后做出的，那么这种做法可能会导致报告偏差。在这里，我们讨论了在报告研究结果时如何平衡清晰性和彻底性，并建议预先定义排除实验的标准可能有助于研究人员实现这种平衡。
