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A note on calibration weightings for stratified double sampling with equal probability

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  • Etebong P. Clement

Abstract

This study proposes a more efficient calibration estimator for estimating population mean in stratified double sampling using new calibration weights. The variance of the proposed calibration estimator has been derived under large sample approximation. Calibration asymptotic optimum estimator and its approximate variance estimator are derived for the proposed calibration estimator and existing calibration estimators in stratified double sampling. Analytical results showed that the proposed calibration estimator is more efficient than existing members of its class in stratified double sampling. Analysis and evaluation are presented.

Suggested Citation

  • Etebong P. Clement, 2018. "A note on calibration weightings for stratified double sampling with equal probability," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(12), pages 2835-2847, June.
    • Handle: RePEc:taf:lstaxx:v:47:y:2018:i:12:p:2835-2847
    DOI: 10.1080/03610926.2017.1342836
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