UTILIZATION OF NON-RESPONSE AUXILIARY POPULATION MEAN IN IMPUTATION FOR MISSING OBSERVATIONS
Keywords:
Imputation, Non-response, Post-stratification, Simple Random Sampling Without Replacement (SRSWOR), Respondents (R)Abstract
This paper presents an imputation based factor-type class of estimation strategy for estimating population mean in presence of missing values of auxiliary variable. The non-sampled part of population is used as an imputation technique in the form of a proposed class of estimators. The bias and mean squared error of this class is obtained. Some special cases are discussed. A specific range of parameter is found where the proposed class is optimal. The efficiency of the proposed estimator is compared with similar non-imputed estimator and it is found useful under missing observations setup.
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