One-sided tests in shared frailty models
One-sided tests in shared frailty models
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DOI：
10.1007/s11749-006-0023-9
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发表时间：
2008-05-01
期刊：
影响因子：
1.3
通讯作者：
Janssen, Paul
中科院分区：
文献类型：
--
作者：
Claeskens, Gerda;Nguti, Rosemary;Janssen, Paul
脆弱性模型中异质性存在的检验使用备择假设，其中异质性参数受到不等式约束。因此，经典的似然比渐近卡方分布理论不再成立。我们的主要结果陈述了单侧检验问题的似然比和得分统计量的极限分布。所得分布是卡方分布随机变量的混合。结果显示伽玛和正稳定脆弱分布，并举行时，协变量信息。一个数据示例说明了测试。我们还评估，在一个模拟研究中，关于显着性水平和功率的测试的性能。
Tests for the presence of heterogeneity in frailty models use an alternative hypothesis in which the heterogeneity parameter is subject to an inequality constraint. As a result, the classical likelihood ratio asymptotic chi-square distribution theory is no longer valid. Our main result states the limiting distribution of the likelihood ratio and score statistic for the one-sided testing problem. The resulting distribution is a mixture of chi-square distributed random variables. The results are shown for gamma and positive stable frailty distributions, and hold when covariate information is present. A data example illustrates the tests. We also assess, in a simulation study, the performance of the tests regarding the significance level and power.