One way to protect an interviewee’s privacy when responding to a sensitive questions is through the use of a method called Randomized Response Technique (RRT). There are many different models/ techniques developed by many researchers to estimate the prevalence of a sensitive attribute in a population of humans while protecting the privacy of the individuals. Newly suggested estimators are generally compared with pre-existing estimators on the basis of variance or mean squared error. In this thesis, we propose improvements in certain existing randomized response models that enable them to perform more efficiently than their competitors. The improved performance is established by simulating the results of altering various parameters.
July 3, 2014
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