A new improved estimator of population mean in partial additive randomized response models

被引:2
|
作者
Ozgul, Nilgun [1 ]
Cingi, Hulya [1 ]
机构
[1] Hacettepe Univ, Dept Stat, TR-06800 Ankara, Turkey
来源
HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS | 2017年 / 46卷 / 02期
关键词
Randomized response models; Sensitive question; Auxiliary variable; Efficiency; Mean square error; QUANTITATIVE DATA;
D O I
10.15672/HJMS.2017.414
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In this study, we have developed a new improved estimator for the population mean estimation of the sensitive study variable in Partial Additive Randomized Response Models (RRMs) using two non-sensitive auxiliary variables. The mean squared error of the proposed estimator is derived and compared with other existing estimators based on the auxiliary variable. The proposed estimator is compared with [19],[5] and [13] estimators in performing a simulation study and is found to be more efficient than other existing estimators using non-sensitive auxiliary variable. The results of the simulation study are discussed in the final section.
引用
收藏
页码:325 / 338
页数:14
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