A score test for zero-inflation in correlated count data
A score test for zero-inflation in correlated count data
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DOI：
10.1002/sim.2308
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发表时间：
2006-05-30
影响因子：
2
通讯作者：
McLachlan, Geoffrey J.
中科院分区：
文献类型：
--
作者：
Xiang, Liming;Lee, Andy H.;McLachlan, Geoffrey J.
为了解释零计数和观测同时相关的优势，一类零膨胀泊松混合回归模型适用于适应簇内依赖。本文提出了一种零通货膨胀的分数检验方法，用于评估带有多余零的相关计数数据。通过仿真研究对检验统计量的抽样分布和幂进行了评价。结果表明，该检验统计量在广泛的条件下表现令人满意。测试程序进一步说明使用数据集反复尿路感染。版权所有(c) 2005 John Wiley & Sons, Ltd。
To account for the preponderance of zero counts and simultaneous correlation of observations, a class of zero-inflated Poisson mixed regression models is applicable for accommodating the within-cluster dependence. In this paper, a score test for zero-inflation is developed for assessing correlated count data with excess zeros. The sampling distribution and the power of the test statistic are evaluated by simulation studies. The results show that the test statistic performs satisfactorily under a wide range of conditions. The test procedure is further illustrated using a data set on recurrent urinary tract infections. Copyright (c) 2005 John Wiley & Sons, Ltd.