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Randomized response: Estimating mean square errors of linear estimators and finding optimal unbiased strategies

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Summary

General procedures are described to generate quantitative randomized response (RR) required to estimate the finite population total of a sensitive variable. Permitting sample selection with arbitrary probabilities a formula for the mean square error (MSE) of a linear estimator of total based on RR is noted indicating the simple modification over one that might be based on direct response (DR) if the latter were available. A general formula for an unbiased estimator of the MSE is presented. A simple approximation is proposed in case the RR ratio estimator is employed based on a simple random sample (SRS) taken without replacement (WOR). Among sampling strategies employing unbiased but not necessarily linear estimators based on RR, certain optimal ones are identified under two alternative models analogously to well-known counterparts based on DR, if available. Unlike Warner’s (1965) treatment of categorical RR we consider quantitative RR here.

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  1. Indian Statistical Institute, 203, Barrackpore Trunk Road, 700035, Calcutta, India

    A. Chaudhuri

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  1. A. Chaudhuri
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Chaudhuri, A. Randomized response: Estimating mean square errors of linear estimators and finding optimal unbiased strategies. Metrika 39, 341–357 (1992). https://doi.org/10.1007/BF02614017

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  • DOI: https://doi.org/10.1007/BF02614017

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