Enhanced Estimators and Effective Estimation Procedures for Population Variance under Missing at Random Data in Successive Sampling

Abstract

This paper explores some potent estimation procedures of population variance under missing at random situations in two-occasion successive sampling. Information on auxiliary variables has been involved in supporting for effective estimation of some chain-type exponential and regression estimators under the assumption of sampling units on which information of study variables cannot be obtained due to missing at random. The non-respondents follow the Binomial type of distribution in the estimation. The proposed estimators are compared with the competent estimators under a complete response of sample units. The Empirical studies support theoretical results in the present probability of non-respondent. Results have been interpreted and suitable recommendations are made for data practitioners.