Stratified inverse sampling
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2010
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2553
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eng
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xi, 130 leaves : ill. ; 30 cm.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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National Institute of Development Administration. Library and Information Center
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Prayad Sangngam (2010). Stratified inverse sampling. Retrieved from: http://repository.nida.ac.th/handle/662723737/403.
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Stratified inverse sampling
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Abstract
This dissertation is concerned with stratified inverse sampling and four different sampling schemes are considered, namely inverse random sampling with replacement, inverse random sampling without replacement, inverse PPS sampling with replacement and inverse PPS sampling without replacement. Unbiased estimators of the mean of a study variable in the whole population, the number of units in a class of interest and the prevalence of a characteristic are given together with their unbiased variance estimators. Estimation of the mean per unit in the class of rare units is also presented and the bound of its bias derived. A simulation study was employed to study the properties of these sampling designs and the results of this indicate that inverse sampling without replacement is more efficient than inverse random sampling with replacement. Inverse PPS sampling with replacement gave higher efficiencies to estimates than inverse random sampling with replacement when the correlation coefficient between the auxiliary and study variables is large. In addition, inverse PPS sampling without replacement is more efficient than inverse random sampling without replacement when the correlation coefficient between the auxiliary and study variables is high. When the number of sampled units in a class of interest increases, the variance and mean squared error of the estimator decrease.
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Thesis (Ph.D. (Statistics))--National Institute of Development Administration, 2010