Toward customer-centric organizational science: A common language effect size indicator for multiple linear regressions and regressions with higher-order terms.
开发了一个通用语言效应量指标CLβ，用于更直观地解释多元线性回归和含交互项、非线性项的回归结果，帮助研究者向实践者传达研究发现。
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