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Scrambled Randomized Response Models for Estimating the Mean of a Sensitive Quantitative Variable

Housila P. Singh, Preeti Patidar

Abstract



This paper point out the issue of estimating the mean of a quantitative sensitive variable (QSV) based on scrambled randomized response models (SRRMs). Diana and Perri (DP) (2010) have introduced three SRRM and suggested estimators for mean of the QSV along with their properties. Keeping the studies carried out by Saha (S.) (2007) and DP (2010) in this assessment, we have propounded some modified SRRMs and estimators based on them along with their properties. We have shown that the proposed models and the resulting estimators are more efficient than the S. (2007) and DP (2010) models and the estimators based on them under some truthful conditions. In support of the present analysis, numerical illustrations are given.

Keywords


QSV, SRRM, Estimators, Variance, Efficiency comparison.

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