A note on randomized response models for quantitative data

Shaul K. Bar-Lev (), Elizabeta Bobovitch and Benzion Boukai

Metrika: International Journal for Theoretical and Applied Statistics, 2004, vol. 60, issue 3, 255-260

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. Copyright Springer-Verlag 2004

Date: 2004
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DOI: 10.1007/s001840300308

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