On Generalized Additive Scrambled Response Modeling in Sensitive Surveys
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.
URI
https://app.trdizin.gov.tr/publication/paper/detail/TXpJME5EQTRPQT09http://hdl.handle.net/20.500.12481/2563
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