Some imputation methods to deal with the issue of missing data problems due to random non-response in two-occasion successive sampling

Missingness or incompleteness of data is a challenge to the survey statisticians in producing the reliable estimates of the desired population parameters. If the missingness pattern is unidentifiable, this is the case of random non-response and to deal with such situations, this work proposes some alternative imputations methods to cope with the missing data. The proposed imputation methods result in some efficient estimation procedures of the current population mean in two-occasion successive sampling. The properties of the resultant estimation procedures have been examined and supplemented with empirical studies. Results have been critically analyzed, and recommendations are made to the survey practitioners.