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Likelihood Ratio Type Two-Sample Tests for Current Status Data

机译:当前状态数据的似然比类型两样本测试

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摘要

We introduce fully non-parametric two-sample tests for testing the null hypothesis that the samples come from the same distribution if the values are only indirectly given via current status censoring. The tests are based on the likelihood ratio principle and allow the observation distributions to be different for the two samples, in contrast with earlier proposals for this situation. A bootstrap method is given for determining critical values and asymptotic theory is developed. A simulation study, using Weibull distributions, is presented to compare the power behaviour of the tests with the power of other non-parametric tests in this situation.
机译:我们引入了完全非参数的两样本检验,用于检验零假设(假设样本仅通过当前状态检查间接给出),这些假设来自相同的分布。这些测试基于似然比原理,并且与这种情况下的早期建议相比,这两个样本的观察值分布不同。给出了一种用于确定临界值的自举方法,并发展了渐近理论。提出了使用威布尔分布的仿真研究,以比较这种情况下测试的功效与其他非参数检验的功效。

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