IMPUTATION OF MISSING VALUES BY USING RAW MOMENTS

Sohail Muhammed Umair (), Shabbir Javid and Sohil Fariha
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Sohail Muhammed Umair: Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan .
Shabbir Javid: Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan .
Sohil Fariha: Department of Education, Government College University, Faisalabad, Pakistan .

Statistics in Transition New Series, 2019, vol. 20, issue 1, 21-40

Abstract: 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.

Keywords: non-response; imputation; raw moments; relative efficiency; 62D05 (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:20:y:2019:i:1:p:21-40:n:7

DOI: 10.21307/stattrans-2019-002

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