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Test inversion bootstrap confidence intervals

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In this paper we explore the theoretical and practical implications of using bootstrap test inversion to construct confidence intervals. In the presence of nuisance parameters, we show that the coverage error of such intervals is O(n−1/2) which may be reduced to O(n−1) if a Studentized statistic is used. We present three simulation studies and compare the performance of test inversion methods with established methods on the problem of estimating a confidence interval for the dose–response parameter in models of the Japanese atomic bomb survivors data.

Keywords: Bootstrap t; Edgeworth expansion; Lifespan study; Robbins–Monro algorithm; Test inversion bootstrap; Variance stabilizing transformation

Document Type: Original Article


Affiliations: London School of Hygiene and Tropical Medicine, UK

Publication date: 1999-01-01

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