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Some improved and alternative imputation methods for finite population mean in presence of missing information

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  • Garib Nath Singh
  • Awadhesh K. Pandey
  • Anup Kumar Sharma

Abstract

The crux of this study is to propose some modified and improved compromised imputation methods and their corresponding point estimators to estimate the population mean using information on an auxiliary variable in case of missing data problem under simple random sampling without replacement scheme. The properties of the suggested estimation procedures have been examined. Monte Carlo simulation study has been performed in order to show that the proposed class of estimators give better results in comparison to some of the existing estimators. Suitable recommendations are made to the survey practitioners.

Suggested Citation

  • Garib Nath Singh & Awadhesh K. Pandey & Anup Kumar Sharma, 2021. "Some improved and alternative imputation methods for finite population mean in presence of missing information," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(19), pages 4401-4427, August.
  • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:19:p:4401-4427
    DOI: 10.1080/03610926.2020.1713375
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