Missing Information in Survey Research

本研究开发了新的方法和统计技术来处理调查和其他微观层面数据源的“缺失数据”。在政治学中，大多数研究人员在遇到缺失的数据时使用“列表删除”，但这浪费了宝贵的信息，并可能使关于政治世界的结论产生偏差。虽然统计文献包括一些有吸引力的方法来解决丢失数据的问题，但这些方法的几个重要的理论困难，以及缺乏公开可用的软件，阻碍了这些方法的使用。这个项目概括了使用政治科学数据的不同方法。与此同时，这个项目发展了可以同时应用于综合数据（例如，选举结果或人口普查计数）和调查研究的方法。

This research develops new methodological and statistical techniques to handle `missing data` for survey and other micro-level data sources. In Political Science most researchers use `listwise deletion` when encountering missing data, but this wastes valuable information and can bias conclusions drawn about the political world. While the statistical literature includes some attractive approaches to the missing data problem, several important theoretical difficulties with these approaches, and the lack of publicly available software, prevent these methods from being used. This project generalizes the different approaches for use with political science data. At the same time this project develops methods that can be applied simultaneously to both aggregate data (e.g., electoral results or census counts) and survey research.