One-Sided Coverage Intervals for a Proportion Estimated from a Stratified Simple Random Sample |
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Authors: | Phillip S Kott Yan K Liu |
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Institution: | National Agricultural Statistics Service, 3251 Old Lee Highway, Fairfax, VA 22030, USA E-mail:;Internal Revenue Service, P.O. Box 2608, Washington, DC 20013, USA |
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Abstract: | Using an Edgeworth expansion to speed up the asymptotics, we develop one-sided coverage intervals for a proportion based on a stratified simple random sample. To this end, we assume the values of the population units are generated from independent random variables with a common mean within each stratum. These stratum means, in turn, may either be free to vary or are assumed to be equal. The more general assumption is equivalent to a model-free randomization-based framework when finite population correction is ignored. Unlike when an Edgeworth expansion is used to construct one-sided intervals under simple random sampling, it is necessary to estimate the variance of the estimator for the population proportion when the stratum means are allowed to differ. As a result, there may be accuracy gains from replacing the normal z -score in the Edgeworth expansion with a t -score. |
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Keywords: | Edgeworth expansion effective degrees of freedom model |
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