In social science research, interference between units is the rule rather than the exception. Contagion represents one key causal mechanism of such spillover effects, where one's treatment affects the outcome of another individual indirectly by changing the treated unit's own outcome. Alternatively, the treatment of one individual can affect the outcome of another person through other mechanisms. We consider the identification and sensitivity analysis of contagion effects. We analyse a randomized placebo‐controlled trial of the get out the vote campaign, in which canvassers were sent to randomly selected households with two registered voters but encouraged only one voter within each household to turn out in an upcoming election. To address the problem of non‐compliance, the experiment includes a placebo arm, in which canvassers encourage voters to recycle. We show how to identify and estimate the average contagion and direct effects by decomposing the average spillover effect. Our analysis examines whether canvassing increases the turnout of a non‐contacted voter by altering the vote intention of a contacted voter or through other mechanisms. To address the potential violation of key identification assumptions, we propose non‐parametric and parametric sensitivity analyses. We find robust contagion effects among some households.

中文翻译：

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随机安慰剂对照试验中传染效应的鉴定和敏感性分析

在社会科学研究中，单位之间的干涉是规则而不是例外。传染是这种溢出效应的一个关键因果机制，其中一个人的治疗通过改变治疗单位自身的结果而间接影响另一个人的结果。或者，对一个人的治疗可以通过其他机制影响另一个人的结果。我们考虑对传染效应的识别和敏感性分析。我们分析了退出投票运动的随机安慰剂对照试验，在该试验中，将帆布器发送给了具有两个注册选民的随机选择的家庭，但鼓励每个家庭中只有一名选民参加即将举行的选举。为了解决违规问题，该实验包括一个安慰剂臂，在其中，拉票员鼓励选民进行回收利用。我们展示了如何通过分解平均溢出效应来识别和估计平均传染性和直接效应。我们的分析检查了拉票是否通过改变接触选民的投票意图或通过其他机制来增加非接触选民的投票率。为了解决可能违反关键标识假设的情况，我们提出了非参数和参数敏感性分析。我们发现某些家庭之间的传染病效应很强。为了解决可能违反关键标识假设的情况，我们提出了非参数和参数敏感性分析。我们发现某些家庭之间的传染病效应很强。为了解决可能违反关键标识假设的情况，我们提出了非参数和参数敏感性分析。我们发现某些家庭之间的传染病效应很强。