Locally Optimal Design for A/B Tests in the Presence of Covariates and Network Dependence
Locally Optimal Design for A/B Tests in the Presence of Covariates and Network Dependence
复制标题
存在协变量和网络依赖性的情况下 A/B 测试的局部最优设计
DOI：
10.1080/00401706.2022.2046169
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发表时间：
2022
期刊：
影响因子：
2.5
通讯作者：
Kang, Lulu
中科院分区：
文献类型：
--
作者：
Zhang, Qiong;Kang, Lulu
A/B测试是一种简单的对照实验，是指通过实验对两种处理方法进行比较的统计过程。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在无向网络上连接，并且两个连接的用户的响应是相关的。我们在一个条件自回归模型中包含了处理分配、协变量特征和网络连接。在此模型的基础上，我们提出了一个设计准则来衡量估计治疗效果的方差，并通过最小化标准来分配治疗设置给测试对象。由于设计准则依赖于一个未知的网络相关参数，我们采用局部最优设计方法，并发展了一种混合优化方法来获得最优设计。通过合成和真实的社会网络实例，我们证明了在设计A/B实验时包含网络依赖的价值，并验证了所提出的局部最优设计对参数选择的鲁棒性。本文的补充材料可在网上获得。
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 article, 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. Supplementary materials for this article are available online.
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