An estimation of a sensitive attribute using adjusted Kuk’s randomization device with stratified unequal probability sampling

Abstract

In this article, we develop the estimation of the sensitive attribute proportion of the population which is composed of several clusters by applying unequal probability sampling to the Su et al.’s model which is an adjusted Kuk’s model. We estimate the sensitive parameter, its variance and variance estimator for each unequal probability sampling and two-stage equal probability sampling. We extend our model to the case of stratified unequal probability sampling and stratified two-stage equal probability one. Finally, we compare the efficiency of the two sensitive estimators, one is obtained by unequal probability sampling and the other is obtained by stratified unequal probability sampling.