Bayesian estimation of population proportion in Kim and Warde mixed randomized response technique

Authors

  • Zawar Hussain Quaid-i-Azam University
  • Javid Shabbir Quaid-i-Azam University

DOI:

https://doi.org/10.1285/i20705948v5n2p213

Keywords:

Bayesian estimation, Mean squared error, Randomized response technique, Simple random sampling.

Abstract

In this study, we have developed the Bayesian estimator of the population proportion of a sensitive characteristic when data are obtained through the Randomized Response Technique (RRT) proposed by Kim and Warde (2005). Superiority of the Bayesian estimators is established for a wide range of the values of the population proportion using simple Beta prior information.  It is observed that Bayesian estimators are better than the usual Maximum Likelihood Estimator (MLE) for small as well as moderate samples. The Proposed estimator is also compared with the Warner (1965), Kim and warde (2005) and Kim et al. (2006) estimators.

Author Biographies

Zawar Hussain, Quaid-i-Azam University

Statistics, Assistant Professor

Javid Shabbir, Quaid-i-Azam University

Statistics, Professor

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Published

14-10-2012