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Activity Number:
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52
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Type:
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Topic Contributed
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Date/Time:
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Sunday, July 29, 2007 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #309297 |
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Title:
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Optimal Allocation for Unbalanced Stratified Ranked Set Sample
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Author(s):
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Chris Sroka*+ and Elizabeth A. Stasny and Douglas Wolfe
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Companies:
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The Ohio State University and The Ohio State University and The Ohio State University
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Address:
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1958 Neil Avenue, Columbus, OH, 43210-1247,
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Keywords:
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Neyman allocation ; stratification ; judgment order statistic ; variance estimation
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Abstract:
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Stratified ranked set sampling is a data collection method that stratifies the population before conducting ranked set sampling (RSS). It is similar to traditional stratified sampling, except that RSS is used in place of simple random sampling. This method of sampling results in more precise estimators of the mean than traditional stratified sampling or RSS alone. This sampling method raises an interesting question about how to allocate a fixed sample size to both the strata and the ranks within each stratum. We examine possible allocation schemes to find the method that produces the lowest variance of the mean estimator.
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