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Imputation Of Missing Values By Using Raw Moments

Author

Listed:
  • 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 .)

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.

Suggested Citation

  • Sohail Muhammed Umair & Shabbir Javid & Sohil Fariha, 2019. "Imputation Of Missing Values By Using Raw Moments," Statistics in Transition New Series, Polish Statistical Association, vol. 20(1), pages 21-40, March.
    • Handle: RePEc:vrs:stintr:v:20:y:2019:i:1:p:21-40:n:7
    DOI: 10.21307/stattrans-2019-002
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    References listed on IDEAS

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    1. Abdul Haq & Manzoor Khan & Zawar Hussain, 2017. "A new estimator of finite population mean based on the dual use of the auxiliary information," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(9), pages 4425-4436, May.
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    More about this item

    Keywords

    non-response; imputation; raw moments; relative efficiency; 62D05;
    All these keywords.

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