Some ratio type estimators for estimating the population mean in case of missing data

Document Type : Original Article

Authors

Ajeet Kumar Singh ¹

Himanshi Kumawat ²

¹ Department of Statistics‎, ‎University of Rajasthan‎, ‎Jaipur‎, ‎India

² ‎Department of Statistics‎, ‎University of Rajasthan‎, ‎Jaipur‎, ‎India

10.22067/smps.2025.95580.1052

Abstract

‎This paper investigates ratio-type estimators for estimating the population mean in the presence of missing data‎. ‎To address the problem of missing observations‎, ‎a class of generalized estimators is proposed‎. ‎The bias and mean squared error of the proposed estimators are derived under optimal conditions using first-order approximations‎. ‎The performance of the proposed estimators is then evaluated and compared with that of the classical mean estimator‎, ‎the ratio estimator‎, ‎and the compromised estimator using several empirical data sets‎. ‎The results show that the proposed estimators outperform the existing estimators in terms of efficiency‎.
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Keywords

Bias

‎Imputation‎

‎Mean squared error

‎Percent relative efficiency

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