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

Authors : Nilgun OZGUL, Hulya CİNGİ

Pages : 325-338

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Publication Date : 2017-04-01

Article Type : Research Paper

Abstract :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 insert ignore into journalissuearticles values(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.
Keywords : Randomized response models, Sensitive question, Auxiliary variable, Efficiency, Mean square error