On the efficiency of modified regression-type mean imputation scheme under two-phase sampling (CaJoST, 2023)
Human-based surveys such as medical and social science surveys are oftencharacterized by non-response or missing observations. In this study, a newclass of regression-type mean imputation method that uses n x as anestimate of X was suggested. Using partial derivative approach, the MSEsof the class of estimators presented were derived up to first orderapproximation under two cases. Case I: when the secondary sample 2 S ofsize n   1 nn is a subset of preliminary sample 1S   21SS , andCase 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 otherestimators studied were derived. The results of numerical examples throughsimulations revealed that the suggested class of estimators is more efficient.