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A general bootstrap algorithm for hypothesis testing. (English) Zbl 1231.62078
Summary: The bootstrap is a intensive computer-based method originally mainly devoted to estimate standard deviations, confidence intervals and bias of the studied statistic. This technique is useful in a wide variety of statistical procedures, however, its use for hypothesis testing, when the data structure is complex, is not straightforward and each case must be particularly treated. A general bootstrap method for hypothesis testing is studied. The considered method preserves the data structure of each group independently and the null hypothesis is only used in order to compute the bootstrap statistic values (not at the resampling, as usual). The asymptotic distribution is developed and several case studies are discussed.

MSC:
62G09 Nonparametric statistical resampling methods
62G10 Nonparametric hypothesis testing
62E20 Asymptotic distribution theory in statistics
62N03 Testing in survival analysis and censored data
Software:
bootstrap
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References:
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