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Coverage probability
About: Coverage probability is a research topic. Over the lifetime, 2479 publications have been published within this topic receiving 53259 citations.
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TL;DR: In the analysis of panel data that includes a time-varying covariate, a Hausman pretest is commonly used to decide whether subsequent inference is made using the random effects model or the fixed effects model as discussed by the authors.
17 citations
TL;DR: Wald-type, logarithmic transformation, and Fieller-type statistics for the classical 2-sided equivalence testing of the rate ratio under matched-pair designs with a binary end point are compared.
Abstract: In this article, we compare Wald-type, logarithmic transformation, and Fieller-type statistics for the classical 2-sided equivalence testing of the rate ratio under matched-pair designs with a binary end point These statistics can be implemented through sample-based, constrained least squares estimation and constrained maximum likelihood (CML) estimation methods Sample size formulae based on the CML estimation method are developed We consider formulae that control a prespecified power or confidence width Our simulation studies show that statistics based on the CML estimation method generally outperform other statistics and methods with respect to actual type I error rate and average width of confidence intervals Also, the corresponding sample size formulae are valid asymptotically in the sense that the exact power and actual coverage probability for the estimated sample size are generally close to their prespecified values The methods are illustrated with a real example from a clinical laboratory study
17 citations
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TL;DR: In this article, the authors measure the closeness of the coverage probability, conditional on all of the data, of the adjusted PI and 1-a by measuring the mean square of the difference between this conditional coverage probability and the standard approximate PI.
Abstract: Standard approximate 1-a prediction intervals (PIs) need to be adjusted to take account of the error in estimating the parameters This adjustment may be aimed at setting the (unconditional) probability that the PI includes the value being predicted equal to 1-a Alternatively, this adjustment may be aimed at setting the probability that the PI includes the value being predicted equal to 1-a, conditional on an appropriate statistic T For an autoregressive process of order p, it has been suggested that T consist of the last p observations We provide a new criterion by which both forms of adjustment can be compared on an equal footing This new criterion of performance is the closeness of the coverage probability, conditional on all of the data, of the adjusted PI and 1-a In this paper, we measure this closeness by the mean square of the difference between this conditional coverage probability and 1-a We illustrate the application of this new criterion to a Gaussian zero-mean autoregressive process of order 1-a and one-step-ahead prediction For this example, this comparison shows that the adjustment which is aimed at setting the coverage probability equal to 1-a conditional on the last observation is the better of the two adjustments
17 citations
TL;DR: In this article, three-stage sampling procedures have been developed for both the one-and two-sample situations and discussed with second-order expansions of various characteristics of the proposed procedures including those for the achieved coverage probability in either problem.
Abstract: Fixed-width confidence interval estimation problems for location parameters of negative exponential populations have been studied. Three-stage sampling procedures have been developed for both the one- and two-sample situations. Our discussions are primarily concerned with second-order expansions of various characteristics of the proposed procedures including those for the achieved coverage probability in either problem. Some simulated results are also presented to indicate the usefulness of our procedures for moderate sample sizes.
17 citations
TL;DR: Assuming that the incomplete data are of monotone pattern, a pivotal quantity, similar to the Hotelling T^2 statistic, is proposed and a satisfactory moment approximation to the distribution of the pivotal quantity is derived.
17 citations