论文标题
在有协变量和网络连接的情况下，A/B测试的本地最佳设计
Locally Optimal Design for A/B Testing in the Presence of Covariates and Network Connection
论文作者
论文摘要
A/B测试是一种简单的受控实验类型，是指实验以比较用于测试对象的两种治疗方法的统计程序。例如，许多IT公司经常对连接并形成社交网络的用户进行A/B测试。通常，用户的响应可能与网络连接有关。在本文中，我们假设用户或实验的测试对象连接在一个无向网络上，并且两个连接用户的响应是相关的。我们在条件自回归模型中包括治疗分配，协变量和网络连接。基于此模型，我们提出了一个设计标准，该标准通过最小化标准来衡量估计的治疗效果的方差，并将治疗设置分配给测试对象。由于设计标准取决于未知网络相关参数，因此我们采用本地最佳设计方法，并开发一种混合优化方法来获得最佳设计。通过综合和真实的社交网络示例，我们证明了在设计A/B实验中包括网络依赖性的价值，并验证所提出的本地最佳设计对参数的选择是可靠的。
A/B test, a simple type of controlled experiment, refers to the statistical procedure of experimenting to compare two treatments applied to test subjects. For example, many IT companies frequently conduct A/B tests on their users who are connected and form social networks. Often, the users' responses could be related to the network connection. In this paper, we assume that the users, or the test subjects of the experiments, are connected on an undirected network, and the responses of two connected users are correlated. We include the treatment assignment, covariate features, and network connection in a conditional autoregressive model. Based on this model, we propose a design criterion that measures the variance of the estimated treatment effect and allocate the treatment settings to the test subjects by minimizing the criterion. Since the design criterion depends on an unknown network correlation parameter, we adopt the locally optimal design method and develop a hybrid optimization approach to obtain the optimal design. Through synthetic and real social network examples, we demonstrate the value of including network dependence in designing A/B experiments and validate that the proposed locally optimal design is robust to the choices of parameters.
