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Estimator in Single-Stage Cluster Sampling: Searls Approach | Kongnam | งดใช้ระบบ 3-31 กค 66 Burapha Science Journal

Estimator in Single-Stage Cluster Sampling: Searls Approach

Chatchawan Kongnam, Jirawan Jitthavech, Vichit Lorchirachoonkul

Abstract


This paper presents two population mean estimators using Searls approach in single-stage cluster sampling with simple random sampling without replacement. The first estimator is developed based on the cluster mean when the coefficient of variation of cluster mean is known and the second based on the ratio of the cluster total mean and cluster size mean when the coefficients of variations of cluster total and cluster size are known.               The population for efficiency comparisons of the two proposed estimators is a published data and consists of 20 clusters. Three sample sizes, 5, 10 and 15, are randomly selected from the population and 30 replications are performed for each sample size. It is found that the efficiencies of both estimators using Searls approach are higher than the traditional estimator in all cases under the conditions consistent with the derived conditions.

 

Keywords  :  cluster sampling, coefficient of variation, correlation coefficient, MSE, relative efficiency

 


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References


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