Abstract

 The number of causes that affect the quality of survey and missing data is one of such that keeps sample incomplete. Many imputation methods are available in literature, and are used to replace missing observations like Mean method, Ratio method, Compromised method, Ahmed’s method, Factor-type (F-T) method etc. This paper suggests some new estimation aspects in imputation theory using both, F-T estimator and Compromised estimator. All these are derived from existing procedure of usual Compromised method and found efficient, bias controlled, having many properties. In support of derived results, an empirical study is incorporated over artificial data set showing the efficiency in favour of the suggested methods.

Key words: Estimation, missing data, imputation, bias, mean squared error (m.s.e.), compromised estimator, factor-type (F-T) estimator, factor-type compromised imputation (FTCI).