Testing homogeneity in semiparametric mixture case-control models.
Testing homogeneity in semiparametric mixture case-control models.
复制标题
测试半参数混合病例对照模型的均匀性。
DOI：
10.1080/03610926.2016.1205612
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Liang,Kung-Yee
中科院分区：
文献类型：
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作者：
Di,Chong-Zhi;Chan,KwunChuenGary;Zheng,Cheng;Liang,Kung-Yee
参数和半参数混合模型在许多领域有着广泛的应用，而检验这些模型的齐次性常常是人们感兴趣的问题。然而，假设检验是非标准的，因为在零假设下，一些规律性条件不成立。我们考虑一个半参数混合病例对照模型，在这个意义上，两个分布的密度比被假定为指数形式，而基线密度是未指定的。Qin和Liang（，biometrics）首先考虑了该模型，并提出了一种改进的分数统计量来检验同质性。在这篇文章中，我们考虑基于上确界统计的替代测试程序，这可以提高对某些类型的替代品的能力。我们展示了建议和现有的方法之间的连接和比较。此外，我们提供了一个统一的理论理由的上确界测试和其他现有的测试统计量从经验似然的角度来看。有限样本性能的上确界检验统计量进行了评估，在模拟研究。
Parametric and semiparametric mixture models have been widely used in applications from many areas, and it is often of interest to test the homogeneity in these models. However, hypothesis testing is non standard due to the fact that several regularity conditions do not hold under the null hypothesis. We consider a semiparametric mixture case–control model, in the sense that the density ratio of two distributions is assumed to be of an exponential form, while the baseline density is unspecified. This model was first considered by Qin and Liang (, biometrics), and they proposed a modified score statistic for testing homogeneity. In this article, we consider alternative testing procedures based on supremum statistics, which could improve power against certain types of alternatives. We demonstrate the connection and comparison among the proposed and existing approaches. In addition, we provide a unified theoretical justification of the supremum test and other existing test statistics from an empirical likelihood perspective. The finite-sample performance of the supremum test statistics was evaluated in simulation studies.