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A note on randomized response models for quantitative data

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Abstract.

Standard randomized response (RR) models deal primarily with surveys which usually require a ‘yes’ or a ‘no’ response to a sensitive question, or a choice for responses from a set of nominal categories. As opposed to that, Eichhorn and Hayre (1983) have considered survey models involving a quantitative response variable and proposed an RR technique for it. Such models are very useful in studies involving a measured response variable which is highly ‘sensitive’ in its nature. Eichhorn and Hayre obtained an unbiased estimate for the expectation of the quantitative response variable of interest. In this note we propose a procedure which uses a design parameter (controlled by the experimenter) that generalizes Eichhorn and Hayre’s results. Such a procedure yields an estimate for the desired expectation which has a uniformly smaller variance.

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Correspondence to Shaul K. Bar-Lev.

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Acknowledgements We are grateful to two referees for their valuable and constructive comments.

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Bar-Lev, S., Bobovitch, E. & Boukai, B. A note on randomized response models for quantitative data. Metrika 60, 255–260 (2004). https://doi.org/10.1007/s001840300308

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  • DOI: https://doi.org/10.1007/s001840300308

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