Partial Randomized Response Model for Simultaneous Estimation of Means of Two Sensitive Variables

Abstract

In this study, a new partial randomized response model (RRM) has been proposed for estimating the population mean of two quantitative sensitive variables simultaneously. The utility of proposed model under stratification is also explored. The efficiency comparisons of the proposed model under simple and stratified random sampling are carried out numerically. A real data set was collected through direct questioning, proposed partial RRM and competitor randomized device from the students of statistics and animal sciences departments of Quaid-I-Azam University Islamabad, Pakistan. The performance of the proposed partial RRM is better than competitor RRM under simple and stratified random sampling.

Scrambling Reports: New Estimators for Estimating the Population Mean of Sensitive Variables

“…Warner's proposal for estimating the population proportion π A of a sensitive characteristic A is πA = ρ ys −(1−P) 2P−1 . Extensions to deal with quantitative sensitive variables were developed by Greenberg et al [6], Eriksson et al [7], Huang [8], Bouza [9], Arnab [10], Singh and Gorey [11], Hussain and Shahid [12], Narjis et al [13], Bouza et al [14], Hussain et al [15], and Azeem and Ali [16], among other works. Another utility of RR techniques is their applicability to sensitive issues, such as health areas (see Murtaza et al [17]), social issues (see Chong et al [18]), and drug use (see Perri et al [19] and Kirtasze et al [20]), among other sensitive issues.…”