TY - JOUR
T1 - Exponential-type estimators of the mean of a sensitive variable in the presence of nonsensitive auxiliary information
AU - Koyuncu, Nursel
AU - Gupta, Sat
AU - Sousa, Rita Cristina Pinto de
N1 - SCOPUSID:84893981655
WOS:000336526000004
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Sousa et al. and Gupta et al. suggested ratio and regression-type estimators of the mean of a sensitive variable using nonsensitive auxiliary variable. This article proposes exponential-type estimators using one and two auxiliary variables to improve the efficiency of mean estimator based on a randomized response technique. The expressions for the mean squared errors (MSEs) and bias, up to first-order approximation, have been obtained. It is shown that the proposed exponential-type estimators are more efficient than the existing estimators. The gain in efficiency over the existing estimators has also been shown with a simulation study and by using real data.
AB - Sousa et al. and Gupta et al. suggested ratio and regression-type estimators of the mean of a sensitive variable using nonsensitive auxiliary variable. This article proposes exponential-type estimators using one and two auxiliary variables to improve the efficiency of mean estimator based on a randomized response technique. The expressions for the mean squared errors (MSEs) and bias, up to first-order approximation, have been obtained. It is shown that the proposed exponential-type estimators are more efficient than the existing estimators. The gain in efficiency over the existing estimators has also been shown with a simulation study and by using real data.
KW - Absolute relative bias
KW - Exponential estimator
KW - Mean squared error
KW - Randomized response technique
KW - Regression estimator
UR - http://www.scopus.com/inward/record.url?scp=84893981655&partnerID=8YFLogxK
U2 - 10.1080/03610918.2012.737492
DO - 10.1080/03610918.2012.737492
M3 - Article
SN - 0361-0918
VL - 43
SP - 1583
EP - 1594
JO - Communications In Statistics-Simulation And Computation
JF - Communications In Statistics-Simulation And Computation
IS - 7
ER -