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A predictive estimator of finite population proportion despite missing data

Authors
Journal
Applied Mathematics and Computation
0096-3003
Publisher
Elsevier
Publication Date
Volume
233
Identifiers
DOI: 10.1016/j.amc.2014.01.128
Keywords
  • Superpopulation Models
  • Missing Data
  • Auxiliary Information

Abstract

Abstract This paper considers the problem of estimating a finite population proportion when there are missing values. The prediction approach is used to define a new estimator that presents desirable efficiency properties. Simulation studies are considered to evaluate the performance of the proposed estimator via empirical relative bias and empirical relative efficiency, and favourable results are achieved.

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