Statistical Matching Using File Concatenation With Adjusted Weights and Multiple Imputations
回顾了文件匹配的现有方法，提出并演示了一种通过调整权重和多重插补拼接文件的新方法，其优势在于能展示推断对不可检验假设的敏感性，适用于需要整合多源变量进行推断的研究者。
Abstract Statistically matched files are created in an attempt to solve the practical problem that exists when no single file has the full set of variables needed for drawing important inferences. Previous methods of file matching are reviewed, and the method of file concatenation with adjusted weights and multiple imputations is described and illustrated on an artificial example. A major benefit of this approach is the ability to display sensitivity of inference to untestable assumptions being made when creating the matched file. KEY WORDS: File matchingIncomplete dataMissing dataSensitivity analysis