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Citation Information : Statistics in Transition New Series. Volume 20, Issue 1, Pages 21-40, DOI: https://doi.org/10.21307/stattrans-2019-002
License : (CC BY-NC-ND 4.0)
Published Online: 28-May-2019
The estimation of population parameters might be quite laborious and inefﬁcient, when the sample data have missing values. In comparison follow-up visits, the method of imputation has been found to be a cheaper procedure from a cost point of view. In the present study, we can enhance the performance of imputation procedures by utilizing the raw moments of the auxiliary information rather than their ranks, especially, when the ranking of the auxiliary variable is expensive or difﬁcult to do so. Equations for bias and mean squared error are obtained by large sample approximation. Through the numerical and simulation studies it can be easily understood that the proposed method of imputation can outperform their counterparts.
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