Tests for informative cluster size using a novel balanced bootstrap scheme.
Tests for informative cluster size using a novel balanced bootstrap scheme.
复制标题
使用新颖的平衡引导方案测试信息丰富的簇大小。
DOI：
10.1002/sim.7288
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发表时间：
2017
影响因子：
2
通讯作者：
Datta,Somnath
中科院分区：
文献类型：
--
作者：
Nevalainen,Jaakko;Oja,Hannu;Datta,Somnath
在生物医学研究中经常会遇到被篡改的数据，到目前为止，已经提出了许多方法来分析这些数据。然而，信息簇大小（ICS）现象是一个具有挑战性的问题，它的存在影响了正确分析方法的选择。例如，Dutta和Datta（2015，Biometrics）提出了一些可以测试的边缘分布。根据聚类大小的性质和信息程度，这些边缘分布可能会有所不同，适当测试的选择也是如此。特别是，他们将他们的新测试应用于牙周数据集，其中提到了信息的可扩展性，但没有进行正式的测试。我们提出了自举测试测试ICS的存在。通过将重采样的观测值与紧密匹配的观测值合并，开发了一种平衡bootstrap方法来成功地估计零分布。依赖于集群内的交换的假设，所提出的程序在模拟中表现良好，即使有少量的集群，在不同的分布和对不同的替代假设，从而使其成为一个综合测试。我们还解释了如何将ICS测试扩展到回归设置，从而提高其实际效用。使用前面提到的牙周数据集的方法进行说明。版权所有© 2017约翰威利父子有限公司.
Clustered data are often encountered in biomedical studies, and to date, a number of approaches have been proposed to analyze such data. However, the phenomenon of informative cluster size (ICS) is a challenging problem, and its presence has an impact on the choice of a correct analysis methodology. For example, Dutta and Datta (2015, Biometrics) presented a number of marginal distributions that could be tested. Depending on the nature and degree of informativeness of the cluster size, these marginal distributions may differ, as do the choices of the appropriate test. In particular, they applied their new test to a periodontal data set where the plausibility of the informativeness was mentioned, but no formal test for the same was conducted. We propose bootstrap tests for testing the presence of ICS. A balanced bootstrap method is developed to successfully estimate the null distribution by merging the re‐sampled observations with closely matching counterparts. Relying on the assumption of exchangeability within clusters, the proposed procedure performs well in simulations even with a small number of clusters, at different distributions and against different alternative hypotheses, thus making it an omnibus test. We also explain how to extend the ICS test to a regression setting and thereby enhancing its practical utility. The methodologies are illustrated using the periodontal data set mentioned earlier. Copyright © 2017 John Wiley & Sons, Ltd.