Akande Olanrewaju, Madson Gabriel, Hillygus D Sunshine, Reiter Jerome P
Duke University, Durham NC, USA.
J R Stat Soc Ser A Stat Soc. 2021 Apr;184(2):643-662. doi: 10.1111/rssa.12635. Epub 2021 Jan 9.
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 U.S. Current Population Survey (CPS). In doing so, we examine the sensitivity of results to different assumptions about the unit and item nonresponse.
通常，政府机构和调查组织了解调查中某些变量的人口计数或百分比。这些信息可能来自辅助来源，例如行政数据库或其他高质量调查。我们提出并说明了一个基于模型的框架，用于在处理单位无回答和项目无回答时利用此类辅助边际信息。我们展示了如何利用边际信息为每种无回答类型指定不同的缺失机制。我们使用该框架对美国当前人口调查（CPS）数据子集中的选民投票率缺失值进行插补。在此过程中，我们研究了结果对关于单位无回答和项目无回答的不同假设的敏感性。
