当前位置: X-MOL 学术Leadersh. Q. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Common methodological mistakes
The Leadership Quarterly ( IF 9.924 ) Pub Date : 2023-02-21 , DOI: 10.1016/j.leaqua.2023.101677
Jesper N. Wulff , Gwendolin B. Sajons , Ganna Pogrebna , Sirio Lonati , Nicolas Bastardoz , George C. Banks , John Antonakis

For scientific discoveries to be valid—whether in theory or empirically—a phenomenon must be accurately described: The scientist must use appropriate counterfactuals and eliminate competing explanations. Empirical work must also use an appropriate design and method, and empirical claims made about the phenomenon must be correctly characterized. Moreover, valid empirical discoveries must be reliable in the sense that scientists who reexamine the data must be able to reproduce the finding or to replicate the effect from data gathered in a similar context. Only discoveries adhering to the above criteria can be scientifically informative, serve as building blocks for theory, or have policy implications. Unfortunately, as several recent surveys of the literature show, much of the published works in the management and applied psychology fields are uninformative; contributing reasons include several intractable problems in the study design and analysis as well as the failure of the field to adopt open science practices. Against this backdrop, we identify common methodological mistakes made in applied work. We group these mistakes into three major categories: (a) study design and data collection (e.g., fit between hypotheses and methods, design, measurement, open science, literature reviews), (b) data analysis (e.g., data preprocessing, choice of estimators, analysis of data, issues concerning endogeneity, and use of instrumental variables), and (c) diagnostics, inferences, and reporting. We also explain how to avoid these issues, so that published work makes for a useful contribution to the scientific record.



中文翻译:

常见的方法错误

为了使科学发现有效——无论是在理论上还是在经验上——必须准确地描述一种现象:科学家必须使用适当的反事实并消除相互竞争的解释。实证工作还必须使用适当的设计和方法,并且必须正确地描述关于现象的经验主张。此外,有效的经验发现必须是可靠的,因为重新检查数据的科学家必须能够重现该发现或复制在类似背景下收集的数据的影响。只有符合上述标准的发现才能提供科学信息,作为理论的基石,或具有政策意义。不幸的是,正如最近的几项文献调查所示,许多在管理和应用心理学领域发表的著作都没有提供信息;促成的原因包括研究设计和分析中的几个棘手问题,以及该领域未能采用开放科学实践。在此背景下,我们确定了应用工作中常见的方法论错误。我们将这些错误分为三大类:(a) 研究设计和数据收集(例如,假设和方法之间的匹配、设计、测量、开放科学、文献综述),(b) 数据分析(例如,数据预处理、选择估计量、数据分析、有关内生性的问题和工具变量的使用),以及 (c) 诊断、推论和报告。我们还解释了如何避免这些问题,以便发表的作品对科学记录做出有益的贡献。

更新日期:2023-02-21
down
wechat
bug