Abstract
An effort has been made to develop calibration estimators of the population mean under two-stage stratified random sampling when auxiliary information is available at primary stage unit level. The properties of the developed estimators are derived in terms of design-based approximate variance and approximate consistent design-based estimator of the variance. Some simulation studies have been conducted to investigate the relative performance of calibration estimators over the usual estimator of the population mean without using auxiliary information in two-stage stratified random sampling. It has been found that the two-step calibration estimator has outperformed than the other calibration estimators and the usual estimator without using auxiliary information.
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Sisodia, B.V.S., Singh, D. (2020). Calibration Approach-Based Estimators for Finite Population Mean in Multistage Stratified Random Sampling. In: Chandra, G., Nautiyal, R., Chandra, H. (eds) Statistical Methods and Applications in Forestry and Environmental Sciences. Forum for Interdisciplinary Mathematics. Springer, Singapore. https://doi.org/10.1007/978-981-15-1476-0_7
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