Journal
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Volume 39, Issue 18, Pages 3245-3251Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/03610920903009400
Keywords
Auxiliary information; Efficiency; Imputation methods; Regression type-estimators
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Funding
- Italian Ministry of University and Research
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Motivated by a recent work by Kadilar and Cingi (2008), we proposed three regression-type estimators to overcome the problem of missing data for a study variable. The estimators make optimal use of the available auxiliary information. We show that, given the same amount of information, these estimators are simpler and more efficient than those proposed by Kadilar and Cingi. A numerical illustration, performed on three different populations, highlights the efficiency gain from using our proposal. Finally, a suggestion is made regarding the optimal use of auxiliary information in sampling practice.
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