Department of Clinical Psychopharmacology and Neurotoxicology, National Institute of Mental Health and Neurosciences, Bangalore, India.
J Clin Psychiatry. 2021 Feb 18;82(1):20f13804. doi: 10.4088/JCP.20f13804.
Questionable research practices (QRPs) in the statistical analysis of data and in the presentation of the results in research papers include HARKing, cherry-picking, P-hacking, fishing, and data dredging or mining. HARKing (Hypothesizing After the Results are Known) is the presentation of a post hoc hypothesis as an a priori hypothesis. Cherry-picking is the presentation of favorable evidence with the concealment of unfavorable evidence. P-hacking is the relentless analysis of data with an intent to obtain a statistically significant result, usually to support the researcher's hypothesis. A fishing expedition is the indiscriminate testing of associations between different combinations of variables not with specific hypotheses in mind but with the hope of finding something that is statistically significant in the data. Data dredging and data mining describe the extensive testing of relationships between a large number of variables for which data are available, usually in a database. This article explains what these QRPs are and why they are QRPs. This knowledge must become widespread so that researchers and readers understand what approaches to statistical analysis and reporting amount to scientific misconduct.
可疑的研究实践(QRPs)在数据的统计分析和研究论文结果的呈现中包括 HARKing、选择性分析、P 值操纵、钓鱼和数据挖掘或挖掘。HARKing(结果已知后假设)是将事后假设呈现为先验假设。选择性分析是指只呈现有利的证据而隐瞒不利的证据。P 值操纵是指为了获得有统计学意义的结果而对数据进行无休止的分析,通常是为了支持研究人员的假设。钓鱼式研究是指在没有具体假设的情况下,对不同变量组合之间的关联进行无差别测试,而是希望在数据中找到有统计学意义的东西。数据挖掘和数据挖掘描述了对大量可获得数据的变量之间关系的广泛测试,通常在数据库中进行。本文解释了这些 QRPs 是什么以及为什么它们是 QRPs。这种知识必须广泛传播,以便研究人员和读者了解哪些统计分析和报告方法构成了科学不当行为。