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http://dx.doi.org/10.5351/CSAM.2016.23.1.047

A composite estimator for stratified two stage cluster sampling  

Lee, Sang Eun (Department of Applied and Information Statistics, Kyonggi University)
Lee, Pu Reum (Department of Statistics, Hankuk University of Foreign Studies)
Shin, Key-Il (Department of Statistics, Hankuk University of Foreign Studies)
Publication Information
Communications for Statistical Applications and Methods / v.23, no.1, 2016 , pp. 47-55 More about this Journal
Abstract
Stratified cluster sampling has been widely used for effective parameter estimations due to reductions in time and cost. The probability proportional to size (PPS) sampling method is used when the number of cluster element are significantly different. However, simple random sampling (SRS) is commonly used for simplicity if the number of cluster elements are almost the same. Also it is known that the ratio estimator produces a good performance when the total number of population elements is known. However, the two stage cluster estimator should be used if the total number of elements in population is neither known nor accurate. In this study we suggest a composite estimator by combining the ratio estimator and the two stage cluster estimator to obtain a better estimate under a certain population circumstance. Simulation studies are conducted to compare the superiority of the suggested estimator with two other estimators.
Keywords
post weight adjustment; jackknife method; linear combination; ratio estimator; enumerated district;
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Times Cited By KSCI : 2  (Citation Analysis)
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