On Generalized Additive Scrambled Response Modeling in Sensitive Surveys

Year 2019, Volume: 32 Issue: 1, 372 - 383, 01.03.2019

Waqas Arshad Zawar Hussaın

Abstract

In this article, we use additive scrambling to estimate
the mean of a sensitive variable. In the proposed scrambling model, taking G
(>1 ) as a positive integer chosen by the interviewer, each respondent is
asked to randomly draw G values from
a given distribution of scrambling variable and add average of these randomly
drawn values  to his/her true response on
the sensitive variable. Using repetition of the scrambling experiment, we
propose a relatively more efficient estimator of sensitive mean without
incurring any additional sampling cost. We present a generalization of additive
scrambled response models and show that most of additive scrambling models are
special cases of suggested generalization. Through algebraic and numerical
comparisons, superiority of the proposed methodology is established. 

Keywords

Average, Scrambled response model, Randomized response, Sensitive surveys, , privacy protection

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