Study Of Some General Classes Of Estımator For Estımatıng Populatıon Mean In Compromısed Imputatıon Under TwoPhase Samplıng Scheme
Keywords:
Imputation methods, Bias, Mean Square error, Missing data, Non-response, Simple Random Sampling without Replacement (SRSWOR), EfficiencyAbstract
In this paper, authors have proposed some general classes of estimators for estimating population mean in compromised imputation under the framework of two-phase sampling design in presence of missing values. Two different sampling designs in two-phase sampling are compared under imputed data and their Biases, mean square error (MSE) expressions and percentage relative efficiency (PRE) are obtained. Further, theoretical results stating superiority of the proposed estimators, over the existing estimators have been verified through empirical illustrations based on different data sets from the classical statistical literature.