Swarangi M. Gorey

An efficient stratified randomized response model

This article proposes an efficient stratified randomized response model based on the Mangat et al. model. We have obtained the variance of the proposed estimator of πs, the proportion of the respondents in the population belonging to a sensitive group, under proportional and Neyman allocations. It is shown that the estimator based on the proposed model is more efficient than the Mangat et al. estimator under both proportional as well as Neyman allocations, the Hong et al. estimator, and Kim andWarde’s estimator. We have also examined the superiority of the suggested estimator over the Mangat et al. estimator, the Hong et al. estimator, and Kim and Warde’s estimator with the aid of numerical illustration and pictorial representation.

An efficient new randomized response model

ABSTRACT This paper addresses the problem of estimating the population proportion π of a sensitive group. We have suggested a randomized response (RR) model that is more efficient than the one envisaged by Gjestvang and Singh ([2006), A new randomized response model, Journal of Royal Statistcal Socity, B, (3), 523–530].

Estimation of population proportion of a qualitative character using randomized response technique in stratified random sampling

ABSTRACT This paper proposes an efficient stratified randomized response model based on Chang et al.s (2004) model. We have obtained the variance of the proposed estimator of πs, the proportion of the respondents in the population belonging to a sensitive group, under proportional and Neyman allocations. It is shown that the estimator based on the proposed model is more efficient than the Chang et al.s (2004) estimator under both proportional as well as Neyman allocations, Hong et al.s (1994) estimator and Kim and Wardes (2004) estimator. Numerical illustration and pictorial representation are given in support of the present study.

Efficient estimation of population mean of sensitive variable in presence of scrambled responses

ABSTRACT This paper addresses the problem of estimating the population mean of a sensitive variable in presence of scrambled response. We have suggested a randomized response model which uses known values of mean and variance of scrambling variable. We have shown that the proposed randomized response model is always better than that of Gjestvang and Singhs (2009) and Singh and Tarrays (2014) randomized response models. A numerical study for efficiency comparison is also presented.

A new efficient unrelated randomized response model

ABSTRACT The present paper suggests an interesting and useful ramification of the unrelated randomized response model due to Pal and Singh (2012) [A new unrelated question randomized response model. Statistics 46 (1), 99–109] that can be used for any sampling scheme. We have shown theoretically and numerically that the proposed model is more efficient than Pal and Singh (2012) model.

An Efficient Randomized Response Model Utilizing Higher Order Moments Ratios of Scrambling Variables

ABSTRACT In this paper, we have 89 suggested an improved randomized response (RR) model for estimating π, the proportion of respondents in the population belonging to the sensitive group. We have studied the properties of the RR model. The proposed model is found to be more efficient than the RR model studied by Gjestvang and Singh (2006). Numerical illustration is given in support of the present study.

An improved version of Gjestvang and Singh's randomized response model

This paper suggests an efficient randomized response model. We have studied the properties of the suggested ran- domized response model and compared with Gjestvang and Singh (2009) and Tarray and Singh (2015) model. We have shown theoretically and empirically that the proposed model is more efficient than the Gjestvang and Singh (2009) and Tarray and Singh (2015) randomized response models.