Extending and Implementing Multiple Imputation Technology

多重插值技术是指处理不完整数据的一系列技术。这项创新的技术将在建议的以成绩为基础的更新下得到完善，它将特别适用于用大量公共费用建立的数据库，并将提供给许多数据分析人员及其标准统计软件库。因此，除了对学术研究界的重要性之外，这项创新技术对政府的统计工作也有影响，例如人口普查少计调整和对缺陷数据的类似补偿形式（所谓的“统计修复工作”）。随着数据收集资源的减少和数据丢失问题由于财政和其他限制而成倍增加，这种工作比以往任何时候都更需要。当从广泛的社会调查和临床医疗协议等广泛来源广泛使用的科学数据普遍不完整时，良好的质量分析也受到威胁。

Multiple imputation technology refers to a family of techniques for dealing with incomplete data. This innovative technology, to be perfected under the recommended accomplishment- based renewal, will be especially useful in the context of data bases that have been constructed at great public expense and are to be made available to many data analysts with their arsenals of standard statistical software. Therefore, and in addition to its importance for the academic research community, this innovative technology has implications for statistical endeavors undertaken by government, such as census undercount adjustment and similar forms of compensation for deficient data (so-called "statistical repair work"). Such work is needed more than ever before as data collection resources shrink and missing data problems multiply owing to financial and other restrictions. Good quality analysis is also at stake when, as is becoming increasingly true, incompleteness pervades intensively used scientific data from sources as far-ranging as social surveys and clinical medical protocols.