A New Improved Estimator of Population Mean in Partial Additive Randomized Response Models
Date
2017- Citations
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In this study, we have developed a new improved estimator for the population mean estimation of the sensitive study variable in Partial Additive Randomized Response Models (RRMs) using two non-sensitive auxiliary variables. The mean squared error of the proposed estimator is derived and compared with other existing estimators based on the auxiliary variable. The proposed estimator is compared with [19],[5] and [13] estimators in performing a simulation study and is found to be more efficient than other existing estimators using non-sensitive auxiliary variable. The results of the simulation study are discussed in the final section.
