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 pre- dictive mean matching are outlined
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