Monte Carlo evaluation of resampling-based hypothesis tests

被引：36

作者：

Boos, DD ^{[1
]}

Zhang, J

机构：

[1] N Carolina State Univ, Dept Stat, Raleigh, NC 27695 USA

[2] Merck & Co Inc, Merck Sharp & Dohme Res Labs, Clin Biostat, Rahway, NJ 07065 USA

来源：

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 2000年 / 95卷 / 450期

关键词：

bootstrap; extrapolation; Monte Carlo test; permutation test; p value; power function; SIMEX;

D O I：

10.2307/2669393

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Monte Carlo estimation of the power of tests that require resampling can be very computationally intensive. It is possible to reduce the size of the inner resampling loop as long as the resulting estimator of power can be corrected for bias. A simple linear extrapolation method is shown to perform well in correcting for bias and thus reduces computation time in Monte Carlo power studies.

引用

页码：486 / 492

页数：7

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