Implications of Survey Sampling Design for Missing Data Imputation-调查抽样设计对缺...

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英文文献：Implications of Survey Sampling Design for Missing Data Imputation-调查抽样设计对缺失数据估算的意义
英文文献作者：Gedikoglu, Haluk,Parcell, Joseph L.
英文文献摘要：
Previous studies that analyzed multiple imputation using survey data did not take into account the survey sampling design. The objective of the current study is to analyze the impact of survey sampling design missing data imputation, using multivariate multiple imputation method. The results of the current study show that multiple imputation methods result in lower standard errors for regression analysis than the regression using only complete observation. Furthermore, the standard errors for all regression coefficients are found to be higher for multiple imputation with taking into account the survey sampling design than without taking into account the survey sampling design. Hence, sampling based estimation leads to more realistic standard errors.

以往利用调查数据分析多重估算的研究没有考虑调查抽样设计。本研究的目的是运用多变量多变量归算方法，分析调查抽样设计缺失数据归算的影响。本研究结果表明，多元归算方法对回归分析的标准误差要低于仅使用完全观测的回归分析。此外，研究还发现，考虑调查抽样设计的多元拟合比不考虑调查抽样设计的多元拟合，各回归系数的标准误差均较高。因此，基于抽样的估计会导致更现实的标准误差。

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