Interference occurs between individuals when the treatment (or exposure) of one individual affects the outcome of another individual. Previous work on causal inference methods in the presence of interference has focused on the setting where a priori it is assumed there is 'partial interference,' in the sense that individuals can be partitioned into groups wherein there is no interference between individuals in different groups. Bowers, Fredrickson, and Panagopoulos (2012) and Bowers, Fredrickson, and Aronow (2016) consider randomization-based inferential methods that allow for more general interference structures in the context of randomized experiments. In this paper, extensions of Bowers et al. which allow for failure time outcomes subject to right censoring are proposed. Permitting right censored outcomes is challenging because standard randomization-based tests of the null hypothesis of no treatment effect assume that whether an individual is censored does not depend on treatment. The proposed extension of Bowers et al. to allow for censoring entails adapting the method of Wang, Lagakos, and Gray (2010) for two sample survival comparisons in the presence of unequal censoring. The methods are examined via simulation studies and utilized to assess the effects of cholera vaccination in an individually-randomized trial of 73,000 children and women in Matlab, Bangladesh. This article is protected by copyright. All rights reserved.

中文翻译：

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具有一般干扰和审查的随机化推断


当一个人的治疗（或暴露）影响另一个人的结果时，人与人之间就会发生干扰。先前关于存在干扰的因果推理方法的工作主要集中在先验地假设存在“部分干扰”的情况，即个体可以分为组，其中不同组中的个体之间没有干扰。 Bowers、Fredrickson 和 Panagopoulos (2012) 以及 Bowers、Fredrickson 和 Aronow (2016) 考虑基于随机化的推理方法，这些方法允许在随机实验的背景下使用更通用的干扰结构。在本文中，鲍尔斯等人的扩展。提出了允许受正确审查影响的故障时间结果。允许正确的审查结果具有挑战性，因为基于标准随机化的无治疗效果零假设检验假设个体是否受到审查并不取决于治疗。 Bowers 等人提出的延期。允许审查需要采用 Wang、Lagakos 和 Gray (2010) 的方法，在存在不平等审查的情况下对两个样本的生存率进行比较。这些方法通过模拟研究进行检验，并在孟加拉国马特拉布对 73,000 名儿童和妇女进行的单独随机试验中用于评估霍乱疫苗接种的效果。本文受版权保护。版权所有。