Most project management research focuses almost exclusively on explanatory analyses. Evaluation of the explanatory power of statistical models is generally based on F-type statistics and the R ² metric, followed by an assessment of the model parameters (e.g., beta coefficients) in terms of their significance, size, and direction. However, these measures are not indicative of a model’s predictive power, which is central for deriving managerial recommendations. We recommend that project management researchers routinely use additional metrics, such as the mean absolute error or the root mean square error, to accurately quantify their statistical models’ predictive power.

中文翻译：

---

解释加预测-项目管理研究的逻辑重点

大多数项目管理研究几乎都专注于解释性分析。评估统计模型的解释力通常基于F型统计和R ²度量，然后根据模型参数的重要性，大小和方向对模型参数（例如β系数）进行评估。但是，这些措施并不表示模型的预测能力，这对于得出管理建议至关重要。我们建议项目管理研究人员常规使用其他度量标准，例如平均绝对误差或均方根误差，以准确地量化其统计模型的预测能力。