On the Efficiency of Imputation Estimators using Auxiliary Attribute

Surveys such as medical and social science surveys, conducted by human are often associated with problems of non-response or missing observations. Several schemes and estimators have been suggested by authors like Singh and Horn (2000), Singh et al (2014), Prasad (2017) and several others, to estimate the population in such situations. However, the existing schemes and estimators only consider quantitative auxiliary variables not qualitative. In this study, some imputation methods were studied using auxiliary attribute and two new imputation schemes using auxiliary attribute have been suggested. The properties (bias and MSE) of the proposed estimators were derived up to a first order approximation using Taylor series approach. Conditions for which the proposed estimator more efficient than other estimators considered in the study were also established. Numerical illustration was conducted and the results revealed that the proposed estimator is more efficient.