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

‎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.‎

کلیدواژه ها:

Bias ، ‎Imputation‎ ، ‎Mean squared error ، ‎Percent relative efficiency