Abstract
In this paper, we suggest a new method of constructing an unbiased regression type estimator in randomized response sampling. We introduce two new randomized response estimators, one we created through the utilization of a sum of special products technique and the other through the utilization of the method used for computing a matrix determinant. This new idea of making an unbiased regression type estimator proves to be more efficient with no loss in respondent protection. Analytical comparisons show the proposed unbiased regression type estimator is always more efficient than the considered competitors. The theoretical justification that the proposed estimator has a smaller variance over its competitors is crystal clear, so no simulation study is required. However to study the gain in magnitude of the relative efficiency, a simulation study has been carried out.
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The authors are thankful to the Editor-in-Chief Dr. Dipak K. Dey, an Associate Editor, a referee and Editorial Assistant: Mr. Sarvagnan Subramanian for their comments and help on the original version of this manuscript.
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Arias, R., Sedory, S.A. & Singh, S. An Unbiased Regression Type Estimator In Randomized Response Sampling. Sankhya B 84, 243–258 (2022). https://doi.org/10.1007/s13571-021-00256-z
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DOI: https://doi.org/10.1007/s13571-021-00256-z