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Calibrated random imputation for qualitative data

Authors
Journal
Journal of Statistical Planning and Inference
0378-3758
Publisher
Elsevier
Publication Date
Volume
128
Issue
2
Identifiers
DOI: 10.1016/j.jspi.2003.11.010
Keywords
  • Survey
  • Qualitative Variables
  • Item Non-Response
  • Imputation
  • Calibration
  • Cox Algorithm

Abstract

Abstract In official statistics, when a file of microdata must be delivered to external users, it is very difficult to propose them a file where missing values has been treated by multiple imputations. In order to overcome this difficulty, we propose a method of single imputation for qualitative data that respect numerous constraints. The imputation is balanced on totals previously estimated; editing rules can be respected; the imputation is random, but the totals are not affected by an imputation variance.

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