Missing-Data Adjustments in Large Surveys
Journal of Business and Economic StatisticsPublished 1 July 1988
Roderick J. A. Little
Citations944
SJR quartileQ1
SJR score4.17
SNIP2.29
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TL;DR
Useful properties of a general-purpose imputation method for numerical data are suggested and discussed in the context of several large government surveys and weighting-based analogs to predictive mean matching are outlined.
Abstract
Useful properties of a general-purpose imputation method for numerical data are suggested and discussed in the context of several large government surveys. Imputation based on predictive mean matching is proposed as a useful extension of methods in existing practice, and versions of the method are presented for unit nonresponse and item nonresponse with a general pattern of missingness. Extensions of the method to provide multiple imputations are also considered. Pros and cons of weighting adjustments are discussed, and weighting-based analogs to predictive mean matching are outlined.
Keywords
Social SciencesMathematics
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