Randomized response revisited

Padmawar, V. R.; Vijayan, K.

doi:10.1016/s0378-3758(00)00097-5

Cited by 25 publications

(9 citation statements)

References 4 publications

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“…Therefore, the optimum SSR3 model is always more efficient than the additive and multiplicative models and, consequently from Equations (18) and (19), also than the original model by Saha. Nevertheless, apart from the aforementioned analytical comparisons, we observe that the model can perform better than the additive and multiplicative models also for values of the constant ϕ which are different from the optimum ϕ 0 .…”

Section: Srr3 Model Efficiencymentioning

confidence: 96%

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New scrambled response models for estimating the mean of a sensitive quantitative character

Diana

Perri

2010

Journal of Applied Statistics

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Moving from the scrambling mechanism recently suggested by Saha [25], three scrambled randomized response (SRR) models are introduced with the intent to realize a right trade-off between efficiency and privacy protection. The models perturb the true response on the sensitive variable by resorting to the multiplicative and additive approaches in different ways. Some analytical and numerical comparisons of efficiency are performed to set up the conditions under which improvements upon Saha’s model can be obtained and to quantify the efficiency gain. The use of auxiliary information is also discussed in a class of\ud estimators for the sensitive mean under a generic randomization scheme. The class includes also the three\ud proposed SRR models. Finally, some graphical comparisons are carried out from the double perspective\ud of the accuracy in the estimates and respondents’ privacy protection

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Section: Srr3 Model Efficiencymentioning

confidence: 96%

“…Bar-Lev et al [2] generalized Eichhorn and Hayre's SRR device by introducing a design parameter which is used for randomizing the responses. Further developments on SRR models can be found in [8,[13][14][15][16][17]19,20,24,26].…”

Section: Introductionmentioning

confidence: 99%

New scrambled response models for estimating the mean of a sensitive quantitative character

Diana

Perri

2010

Journal of Applied Statistics

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“…An excellent exposition of modifications on RR techniques and other related works could be referred to Chaudhuri and Mukerjee [6]. Some resent developments are Bhargava and Singh [1], Chua and Tsui [7], Padmawar and Vijayan [12], Singh et al [14], Chang and Huang [2], Chaudhuri [5], Singh et al [13], Huang [10], and Chang et al [3,4], etc. In particular, to quantify the sensitivity level for certain items of inquiry in practice, Gupta et al [9] first shown how an estimator may be developed on the quantitative characteristics.…”

Section: Introductionmentioning

confidence: 99%

Estimation of sensitive quantitative characteristics in randomized response sampling

Huang¹,

Lan

Kuo

2006

Journal of Statistics and Management Systems

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This paper considers the problem of procuring honest responses for sensitive quantitative characteristics. An alternative survey technique is proposed, which enables us to estimate the population mean unbiasedly and to gauge how sensitive a survey topic is. An asymptotically unbiased estimator of sensitivity level is proposed, and conditions for which unbiased estimation for population variance being available is also studied. In addition, an efficiency comparison is worked out to examine the performance of the proposed procedure. It is found that higher estimation efficiency results from higher variation of randomization device.

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“…A number of improvements of RR sampling have been suggested in the literature; see Chaudhuri and Mukerjee [4] for a review. Some recent developments included Bhargava and Singh [1], Chang and Huang [2], Chaudhuri [3], Christofides [5], Chua and Tsui [6], Huang [9], Mahmood et al [10], Mangat et al [11], Padmawar and Vijayan [12], Singh [13], and Singh et al [14], etc.…”

Section: Introductionmentioning

confidence: 99%

A survey technique for procuring honest responses

Huang¹

2005

Journal of Statistics and Management Systems

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This paper considers the problem of unbiased estimation for the proportion of sensitive characteristics. A survey technique without any use of randomization devices is proposed, which is constructed by using an unrelated, innocuous characteristic together with random group strategy. The proposed technique contributes in higher estimation efficiency and better protection for personal privacy, which results in a greater degree of respondents' cooperation. And it may be operated through cheaper approaches such that the survey costs would be reduced.

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Randomized response revisited

Cited by 25 publications

References 4 publications

New scrambled response models for estimating the mean of a sensitive quantitative character

New scrambled response models for estimating the mean of a sensitive quantitative character

Estimation of sensitive quantitative characteristics in randomized response sampling

A survey technique for procuring honest responses

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