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Optimal imputation of the missing data using multi auxiliary information

Author

Listed:
  • Shashi Bhushan

    (Dr. Shakuntala Misra National Rehabilitation University)

  • Abhay Pratap Pandey

    (University of Delhi)

Abstract

This article deals with some new imputation methods by extending the work of Bhushan and Pandey using multi-auxiliary information. The popularly used imputation like mean imputation, ratio method of imputation, regression method of imputation and power transformation method are special cases of the proposed methods apart from being less efficient than the proposed methods. The proposed imputation methods can be considered as an efficient extension to the work of Singh and Deo (Stat Pap 44:555–579, 2003), Singh (Stat A J Theor Appl Stat 43(5):499–511, 2009), Ahmed et al. (Stat Transit 7(6):1247–1264, 2006), Diana and Perri (Commun Stat Theory Methods 39:3245–3251, 2010) and Bhushan and Pandey (J Stat Manag Syst 19(6):755–769, 2016, Commun Stat Theory Methods 47(11):2576–2589, 2018). The theoretical results are derived and comparative study is conducted using real and simulated data and the results are found to be quite encouraging providing the improvement over the all discuss work.

Suggested Citation

  • Shashi Bhushan & Abhay Pratap Pandey, 2021. "Optimal imputation of the missing data using multi auxiliary information," Computational Statistics, Springer, vol. 36(1), pages 449-477, March.
    • Handle: RePEc:spr:compst:v:36:y:2021:i:1:d:10.1007_s00180-020-01016-9
    DOI: 10.1007/s00180-020-01016-9
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    References listed on IDEAS

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    1. Shashi Bhushan & Abhay Pratap Pandey, 2018. "Optimality of ratio type estimation methods for population mean in the presence of missing data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(11), pages 2576-2589, June.
    2. Sarjinder Singh & Balbinder Deo, 2003. "Imputation by power transformation," Statistical Papers, Springer, vol. 44(4), pages 555-579, October.
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