
Locally correct confidence intervals for a binomial proportion: A new criteria for an interval estimator
Wellrecommended methods of forming `confidence intervals' for a binomia...
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The Significance Filter, the Winner's Curse and the Need to Shrink
The "significance filter" refers to focusing exclusively on statisticall...
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Cost Issue in Estimation of Proportion in a Finite Population Divided Among Two Strata
The problem of estimation of the proportion of units with a given attrib...
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An example of application of optimal sample allocation in a finite population
The problem of estimating a proportion of objects with particular attrib...
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Binomial confidence intervals for rare events: importance of defining margin of error relative to magnitude of proportion
Confidence interval performance is typically assessed in terms of two cr...
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Practical Valid Inferences for the TwoSample Binomial Problem
Consider comparing two independent binomial responses. Our interest is w...
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Insights and Inference for the Proportion Below the Relative Poverty Line
We examine a commonly used relative poverty measure H_p, defined to be t...
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Mathematical properties and finitepopulation correction for the Wilson score interval
In this paper we examine the properties of the Wilson score interval, used for inferences for an unknown binomial proportion parameter. We examine monotonicity and consistency properties of the interval and we generalise it to give two alternative forms for inferences undertaken in a finite population. We discuss the nature of the "finite population correction" in these generalised intervals and examine their monotonicity and consistency properties. This analysis gives the appropriate confidence interval for an unknown population proportion or unknown unsampled proportion in a finite or infinite population. We implement the generalised confidence interval forms in a userfriendly function in R.
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