Troendle James F, Yu Kai F
Biometry and Mathematical Statistics Branch, Division of Epidemiology, Statistics, and Prevention Research, National Institute of Child Health and Human Development, National Institutes of Health, DHHS, Bethesda, MD 20892, USA.
Stat Med. 2006 Jul 15;25(13):2284-98. doi: 10.1002/sim.2340.
The classical two-sample problem with random right-censoring is considered. We show that non- parametric likelihood techniques can be used to obtain tests for either the identity hypothesis or the non-parametric Behrens-Fisher hypothesis (NBFH). In the case of the identity hypothesis, a special imputed permutation distribution is used to estimate the distribution under the null hypothesis. In the case of the NBFH, simulation from the constrained non-parametric maximum likelihood estimate is used. Simulation shows that the tests using either approximation have excellent control of the type I error rate, even with quite small sample sizes. Further, for Lehmann-type alternatives the likelihood-based methods have similar power to the logrank test, while for the non-Lehmann-type alternatives tried here the likelihood-based methods have superior power.
考虑具有随机右删失的经典两样本问题。我们表明，非参数似然技术可用于获得针对恒等假设或非参数贝伦斯 - 费希尔假设（NBFH）的检验。在恒等假设的情况下，使用一种特殊的插补置换分布来估计原假设下的分布。在NBFH的情况下，使用从约束非参数最大似然估计进行模拟。模拟表明，即使样本量相当小，使用任何一种近似方法的检验都能很好地控制第一类错误率。此外，对于莱曼型备择假设，基于似然的方法与对数秩检验具有相似的功效，而对于这里尝试的非莱曼型备择假设，基于似然的方法具有更高的功效。
