论文标题
在干涉的情况下，关于Horvitz-Thompson估计量的稀有亚组分析的注释
A note on Horvitz-Thompson estimators for rare subgroup analysis in the presence of interference
论文作者
论文摘要
当受到干扰时，受试者的结果取决于对他人的治疗，治疗效果可能会采取几种不同的形式。这种情况经常出现，尤其是在疫苗评估中。在可能会干扰的情况下，已经提出了两阶段群集随机试验，以估算某些因果关系对比的一种手段。在有限的人群设置中工作，使用文献中建议的一些估计量进行研究，包括文献中建议的估计值，包括Horvitz-Thompson，Hajek，以及所谓的Hudgens and Halloran和Halloran中的边际估计器的自然估计剂的自然扩展。 Horvitz-Thompson风格的估计。我还提供了几个估计器的方差估计器。我表明，Horvitz-Thompson（HT）类型估计量总是没有偏见，无论估算器的兴趣水平如何，都在群体或人群中至少提供一个主题。对于“自然”或hajek样式估计器的情况并非如此，对于稀有子组而言，这通常是不确定的。
When there is interference, a subject's outcome depends on the treatment of others and treatment effects may take on several different forms. This situation arises often, particularly in vaccine evaluation. In settings where interference is likely, two-stage cluster randomized trials have been suggested as a means of estimating some of the causal contrast of interest. Working in the finite population setting to investigate rare and unplanned subgroup analyses using some of the estimators that have been suggested in the literature, include Horvitz-Thompson, Hajek, and what might be called the natural extension of the marginal estimators suggested in Hudgens and Halloran 2008. I define the estimands of interest conditional on individual, group and both individual and group baseline variables, giving unbiased Horvitz-Thompson style estimates for each. I also provide variance estimators for several estimators. I show that the Horvitz-Thompson (HT) type estimators are always unbiased provided at least one subject within the group or population, whatever the level of interest for the estimator, is in the subgroup of interest. This is not true of the "natural" or the Hajek style estimators, which will often be undefined for rare subgroups.
