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Dergiler / Hacettepe Journal of Mathematics and Statistics / 2026 / Volume: 46 Issue: 2

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

Nilgun Ozgul
Hulya Cingi
Sayfa
—
Yayın Tarihi
2017-04-01
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The results of the simulation study are discussed in the final section.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez: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.
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Temel Bulgular & Veri: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.
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Sonuç & Katkı:The results of the simulation study are discussed in the final section.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Randomized response models · Sensitive question · Auxiliary variable

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 (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.

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Bu Makaleye Atıf Yap

Ozgul, N., Cingi, H. (2017). A new improved estimator of population mean in partial additive randomized response models. Hacettepe Journal of Mathematics and Statistics, Volume: 46 Issue: 2. https://ajindex.com/articles/1403056

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