Use of Domain Estimators with Unequal Probability in Sample Surveys
Journal of the American Statistical Association
The phenomenon of nonresponse in a sample survey reduces the precision of parameters estimates and increases bias in estimates resulting in larger mean square error, thus ultimately reducing their efficiency. An important technique to address these problems is by calibration. We proposed calibration estimators for totals of domain of study. Sample designs and in particular sample sizes are chosen so as to provide reliable estimates for domains of study. But budget and other constraints usually
... revent the allocation of sufficiently large samples to domains to provide reliable estimates using traditional statistical techniques. We have developed an approach for finding the best sample design for the domain calibration estimators subject to a cost constraint and derived optimum stratum sample sizes that minimized the variances of the proposed domain calibration estimators and reduced the objective function. The efficacy of the proposed domain calibration estimators was tested through a real data analysis. Results of the analytical study using real data showed that our proposed domain calibration estimator is substantially superior to the traditional GREG-estimator with relatively small bias, mean square error and average length of confidence interval.