Department of Management.
Department of Information Systems and Cyber Security.
J Appl Psychol. 2018 Jun;103(6):659-675. doi: 10.1037/apl0000296. Epub 2018 Jan 22.
To address a long-standing concern regarding a gap between organizational science and practice, scholars called for more intuitive and meaningful ways of communicating research results to users of academic research. In this article, we develop a common language effect size index (CLβ) that can help translate research results to practice. We demonstrate how CLβ can be computed and used to interpret the effects of continuous and categorical predictors in multiple linear regression models. We also elaborate on how the proposed CLβ index is computed and used to interpret interactions and nonlinear effects in regression models. In addition, we test the robustness of the proposed index to violations of normality and provide means for computing standard errors and constructing confidence intervals around its estimates. (PsycINFO Database Record
为了解决组织科学与实践之间长期存在的差距问题，学者们呼吁采用更直观、更有意义的方式将研究结果传达给学术研究的使用者。在本文中，我们开发了一个通用的语言效应大小指数（CLβ），可以帮助将研究结果转化为实践。我们演示了如何计算 CLβ 并将其用于解释多元线性回归模型中连续和分类预测变量的效应。我们还详细说明了如何计算和使用所提出的 CLβ 指数来解释回归模型中的交互作用和非线性效应。此外，我们还测试了所提出的指数对违反正态性的稳健性，并提供了计算其估计值的标准误差和置信区间的方法。
