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• W2331237588 abstract "Stratified random sampling is a powerful sampling strategy to reduce variance of the estimators by incorporating useful auxiliary information to stratify the population. Sample allocation is the one of the important decisions in selecting a stratified random sample. There are two common methods, the proportional allocation and Neyman allocation if we could assume data collection cost for different observation units equal. Theoretically, Neyman allocation considering the size and standard deviation of each stratum, is known to be more effective than proportional allocation which incorporates only stratum size information. However, if the information on the standard deviation is inaccurate, the performance of Neyman allocation is in doubt. It has been pointed out that Neyman allocation is not suitable for multi-purpose sample survey that requires the estimation of several characteristics. In addition to sampling error, non-response error is another factor to evaluate sampling strategy that affects the statistical precision of the estimator. We propose new sample allocation methods using the available information about stratum response rates at the designing stage to improve stratified random sampling. The proposed methods are efficient when response rates differ considerably among strata. In particular, the method using population sizes and response rates improves the Neyman allocation in multi-purpose sample survey." @default.
• W2331237588 created "2016-06-24" @default.
• W2331237588 creator A5047221715 @default.
• W2331237588 creator A5065519901 @default.
• W2331237588 date "2015-12-31" @default.
• W2331237588 modified "2023-09-26" @default.
• W2331237588 title "A Study on Sample Allocation for Stratified Sampling" @default.
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• W2331237588 doi "https://doi.org/10.5351/kjas.2015.28.6.1047" @default.
• W2331237588 hasPublicationYear "2015" @default.
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