EXACT AND ASYMPTOTICALLY ROBUST PERMUTATION TESTS

• 成果类型: Article
• 署名作者: Chung, EunYi; Romano, Joseph P.
• 署名单位: Stanford University; Stanford University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/13-AOS1090
• 发表日期: 2013
• 页码: 484-507
• 关键词: behrens-fisher problem; randomization tests; unequal variances; rank-tests; bootstrap; hypotheses

摘要

Given independent samples from P and Q, two-sample permutation tests allow one to construct exact level tests when the null hypothesis is P = Q. On the other hand, when comparing or testing particular parameters theta of P and Q, such as their means or medians, permutation tests need not be level a, or even approximately level alpha in large samples. Under very weak assumptions for comparing estimators, we provide a general test procedure whereby the asymptotic validity of the permutation test holds while retaining the exact rejection probability alpha in finite samples when the underlying distributions are identical. The ideas are broadly applicable and special attention is given to the k-sample problem of comparing general parameters, whereby a permutation test is constructed which is exact level alpha under the hypothesis of identical distributions, but has asymptotic rejection probability alpha under the more general null hypothesis of equality of parameters. A Monte Carlo simulation study is performed as well. A quite general theory is possible based on a coupling construction, as well as a key contiguity argument for the multinomial and multivariate hypergeometric distributions.