论文标题
在调查中存在影响单元的存在下有效乘以强大的插入
Efficient multiply robust imputation in the presence of influential units in surveys
论文作者
论文摘要
项目无响应是调查中的常见问题。由于未经调整的估计量可能在没有响应的情况下会偏向偏置，因此通常将丢失值归因于尽可能减少无响应偏置的目的。但是，当受访者集中存在有影响力的单位时，常用的插补程序可能会导致人口总数/手段的不稳定估计。在本文中，我们考虑了乘以强大的插定程序的类别，这些程序可为基础模型假设的失败提供一些保护。我们根据条件偏见的概念（一种衡量影响力的概念）开发了有效的乘坐稳定估计器的有效版本。我们介绍了一项模拟研究的结果，以显示拟议方法在偏见和效率方面的益处。
Item nonresponse is a common issue in surveys. Because unadjusted estimators may be biased in the presence of nonresponse, it is common practice to impute the missing values with the objective of reducing the nonresponse bias as much as possible. However, commonly used imputation procedures may lead to unstable estimators of population totals/means when influential units are present in the set of respondents. In this article, we consider the class of multiply robust imputation procedures that provide some protection against the failure of underlying model assumptions. We develop an efficient version of multiply robust estimators based on the concept of conditional bias, a measure of influence. We present the results of a simulation study to show the benefits of the proposed method in terms of bias and efficiency.
