Scrambled Randomized Response Models for Estimating the Mean of a Sensitive Quantitative Variable
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.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.