A score-type test for heterogeneity in zero-inflated models in a stratified population.

A score-type test for heterogeneity in zero-inflated models in a stratified population.
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DOI:
10.1002/sim.6092
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发表时间:
2014-05-30
影响因子:
2
通讯作者:
Todem, David
Todem, David
中科院分区:
医学3区
文献类型:
--
作者:
Cao, Guanqun;Hsu, Wei-Wen;Todem, David

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我们提出了一个分数型统计量来评估异质性在零膨胀模型的计数数据在分层的人口,其中异质性被定义为零计数是从两个来源产生的情况。在这类模型的异质性评价已引起了相当大的关注,在文献中,但现有的检验程序主要依赖于恒定性假设下的备择假设。在本文中,我们扩展了文献描述的分数型检验,以评估同质性对一般的替代品,不忽略分层信息下的备择假设。建议的检验统计量的极限零分布是卡方分布的混合,可以很好地近似一个简单的参数自助程序。我们的数值模拟研究表明,所提出的测试可以大大提高效率的非均匀性测试,忽略了分层信息。经验性的应用龋齿数据在幼儿期进一步显示的重要性和实际效用的方法,在使用分层配置文件,以检测在人口中的异质性。
We propose a score-type statistic to evaluate heterogeneity in zero-inflated models for count data in a stratified population, where heterogeneity is defined as instances in which the zero counts are generated from two sources. Evaluating heterogeneity in this class of models has attracted considerable attention in the literature, but existing testing procedures have primarily relied on the constancy assumption under the alternative hypothesis. In this paper, we extend the literature by describing a score-type test to evaluate homogeneity against general alternatives that do not neglect the stratification information under the alternative hypothesis. The limiting null distribution of the proposed test statistic is a mixture of chi-squared distributions which can be well approximated by a simple parametric bootstrap procedure. Our numerical simulation studies show that the proposed test can greatly improve efficiency over tests of heterogeneity that ignore the stratification information. An empirical application to dental caries data in early childhood further shows the importance and practical utility of the methodology in using the stratification profile to detect heterogeneity in the population.
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