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<p>In this article, an efficient class of product-type compromised methods of imputation has been considered, and their corresponding resultant point estimators have been suggested for missing data in survey sampling. This study gives a first-of-its-kind compromised imputation framework, offering improved efficiency over existing imputation methods. The bias and mean square error expressions for the suggested estimators have been developed. These estimators are more efficient than the mean method of imputation, Singh and Deo (<CitationRef CitationID="CR35">2003</CitationRef>) method of imputation, Shakti (<CitationRef CitationID="CR31">2018</CitationRef>) method of imputation, Prasad and Yadav (<CitationRef CitationID="CR28">2023</CitationRef>) methods of imputation, and adapted estimators for the method of imputation (Pandey and Dubey (<CitationRef CitationID="CR23">1988</CitationRef>), Bahl and Tuteja (<CitationRef CitationID="CR6">1991</CitationRef>), Upadhyaya and Singh (<CitationRef CitationID="CR44">1999</CitationRef>), Singh (<CitationRef CitationID="CR33">2003</CitationRef>), and Singh et&#xa0;al. (<CitationRef CitationID="CR40">2004</CitationRef>)). The numerical illustration and simulation studies illustrate that the proposed estimators are more efficient estimators than the existing estimators in this article.</p>

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An efficient class of product type compromised methods of imputation in survey sampling

  • 期刊论文

  • 发表日期：

    2026年5月14日

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  • Vinay Kumar Yadav,
  • Shakti Prasad

摘要

In this article, an efficient class of product-type compromised methods of imputation has been considered, and their corresponding resultant point estimators have been suggested for missing data in survey sampling. This study gives a first-of-its-kind compromised imputation framework, offering improved efficiency over existing imputation methods. The bias and mean square error expressions for the suggested estimators have been developed. These estimators are more efficient than the mean method of imputation, Singh and Deo (2003) method of imputation, Shakti (2018) method of imputation, Prasad and Yadav (2023) methods of imputation, and adapted estimators for the method of imputation (Pandey and Dubey (1988), Bahl and Tuteja (1991), Upadhyaya and Singh (1999), Singh (2003), and Singh et al. (2004)). The numerical illustration and simulation studies illustrate that the proposed estimators are more efficient estimators than the existing estimators in this article.