Often, government agencies and survey organizations know the population counts or percentages for some of the variables in a survey. These may be available from auxiliary sources, for example administrative databases or other high‐quality surveys. We present and illustrate a model‐based framework for leveraging such auxiliary marginal information when handling unit and item nonresponse. We show how one can use the margins to specify different missingness mechanisms for each type of nonresponse. We use the framework to impute missing values in voter turnout in a subset of data from the US Current Population Survey. In doing so, we examine the sensitivity of results to different assumptions about the unit and item nonresponse.

中文翻译：

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利用不可忽略模型中边际分布的辅助信息来处理项目和单元无响应


通常，政府机构和调查组织知道调查中某些变量的人口数量或百分比。这些可以从辅助来源获得，例如行政数据库或其他高质量的调查。我们提出并说明了一个基于模型的框架，用于在处理单元和项目无响应时利用此类辅助边际信息。我们展示了如何使用边距为每种类型的无响应指定不同的缺失机制。我们使用该框架来估算美国当前人口调查数据子集中选民投票率的缺失值。在此过程中，我们检查结果对有关单位和项目无反应的不同假设的敏感性。