This methods article concerns analysing data generated from running experiments on agent based models to study industries and organisations. It demonstrates that when researchers study virtual ecologies they can and should discard statistical controls in favour of experiment controls. In the first of two illustrations we show that we can detect an effect with a fraction of the data needed for a traditional analysis, which is valuable given the computational complexity of many models. In the second we show that agent based models can provide control without introducing the biases associated with certain causal structures.

翻译：本文是一篇关于分析基于智能体模型运行实验所生成数据的方法论文章，旨在研究产业与组织行为。文章论证了当研究者考察虚拟生态时，可以且应当放弃统计控制而采用实验控制。在第一个示例中，我们证明仅需传统分析所需数据量的一小部分即可检测出效应，这对计算复杂度较高的模型具有重要价值。在第二个示例中，我们表明基于智能体的模型能够提供控制，同时避免由特定因果结构引入的偏差。