A new regression estimator in partial randomized response models

Yıl 2020, Cilt: 22 Sayı: 2, 581 - 590, 10.04.2020

Nilgün Özgül Hülya Çıngı

https://doi.org/10.25092/baunfbed.742610

Öz

In this study, a new regression estimator has been developed with using two non-sensitive auxiliary variables for the population mean estimation of the sensitive study variable in Partial Randomized Response Models (PRRM’s). The proposed estimator is compared with existing estimators based on auxiliary variable in RRM with a simulation study. The proposed estimator is found to be more efficient than other existing estimators.

Anahtar Kelimeler

Sensitive variable, auxiliary variable, regression estimator, randomized response models, efficiency

Kısmi rastgeleleştirilmiş yanıt modellerinde yeni bir regresyon tahmin edicisi

Öz

Bu çalışmada, Kısmi Rastgeleleştirilmiş Yanıt Modellerinde (KRYM), hassas değişkenin kitle ortalamasının tahmini için hassas olmayan iki yardımcı değişken kullanarak yeni bir regresyon tahmin edicisi geliştirilmiştir. Önerilen tahmin edici, simülasyon çalışması yapılarak RYM'de var olan diğer tahmin edicilerle karşılaştırılmış ve önerilen tahmin edicinin var olan diğer tahmin edicilere göre daha etkin olduğu bulunmuştur.

Anahtar Kelimeler

Hassas değişken, yardımcı değişken, regresyon tahmin edicisi rastgeleleştirilmiş yanıt modelleri, etkinlik

Kaynakça

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