(untitled) (CaJoST, 2023)
Human-based surveys such as medical and social science surveys are often characterized by non-response or missing observations. In this study, a new class of regression-type mean imputation method that uses n x as an estimate of X was suggested. Using partial derivative approach, the MSEs of the class of estimators presented were derived up to first order approximation under two cases. Case I: when the secondary sample 2 S of size n   1 nn is a subset of preliminary sample 1S   21SS , and Case II: is when secondary sample 2 S is a subset of universal set N  . Conditions for which the new estimator was more efficient than the other estimators studied were derived. The results of numerical examples through simulations revealed that the suggested class of estimators is more efficient.