Modified Compromized Type Method of Imputation for Estimating Population Mean

Abstract

The study proposed an alternative imputation scheme for the schemes which converged to sample mean as the values of unknown parameters in their estimators converged to zero. The estimator of the population means for the proposed scheme as well as the bias and MSE were derived. The efficiency condition under which the modified estimator is more efficient than existing ones were also presented. Empirical study using four sets of populations was conducted and the results revealed that the proposed estimator was more efficient.

A computational strategy for estimation of mean using optimal imputation in presence of missing observation

“…The introduced estimator is more efficient than the Aliyu et al 24 estimator under the condition if, …”

“…This has also been proven by various authors for ratio and product estimators. Therefore, motivated by Searls 25 and Aliyu et al 24 , we suggest the following imputation strategy for the estimation of as, …”

“…The resultant point estimator of is, where, and are the Searls constants to be obtained so that the MSE of is least and . If , then the suggested estimator reduced to Aliyu et al 24 estimator.…”