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Confidence interval for the bootstrap -value and sample size calculation of the bootstrap test

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  • Jialiang Li
  • Bee Tai
  • David Nott

Abstract

The use of the bootstrap test lends both elegance and simplicity to the analysis of complicated statistical problems. Such a numerical approach yields an estimated P-value as a binomial proportion. The purpose of this article is to recommend that confidence intervals for the bootstrap P-value be calculated routinely. In constructing these intervals, due consideration needs to be given to the P-values that may be close to or equal to zero. We consider three instructive examples and related methods for designing the bootstrap sample size.

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  • Jialiang Li & Bee Tai & David Nott, 2009. "Confidence interval for the bootstrap -value and sample size calculation of the bootstrap test," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(5), pages 649-661.
    • Handle: RePEc:taf:gnstxx:v:21:y:2009:i:5:p:649-661
    DOI: 10.1080/10485250902770035
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    Cited by:

    1. Axel Gandy & Georg Hahn, 2014. "MMCTest—A Safe Algorithm for Implementing Multiple Monte Carlo Tests," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1083-1101, December.

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