Calibration Estimator for Population Mean In Small Sample Size with Nonresponse (Published)
This paper addresses the challenges of estimation of population mean for small or no sample size in the presence of nonresponse and presents a calibration estimator that produces reliable estimates under stratified random sampling from a class of synthetic estimators using calibration approach. Examining the alternative estimator under three distributional assumptions, namely, normal, gamma, and exponential distributions through a simulation analysis with average absolute relative bias, average coefficient of variation, and average mean squared error as evaluation criteria, the results show that it has a consistent estimates of the mean with less bias and greater gain in efficiency. Further validation through the coefficient of variation also shows that the estimator exhibits a more preferred coefficient of variations suitable for small area estimation.
Keywords: calibration, distance measure, nonresponse, small area estimation, synthetic estimators.