In multi-center studies, the presence of a cluster effect leads to correlation among outcomes within a center and requires different techniques to handle such correlation. Testing for a cluster effect can serve as a pre-screening step to help guide the researcher towards the appropriate analysis. With time to event data, score tests have been proposed which test for the presence of a center effect on the hazard function. However, sometimes researchers are interested in directly modeling other quantities such as survival probabilities or cumulative incidence at a fixed time. We propose a test for the presence of a center effect acting directly on the quantity of interest using pseudo-value regression, and derive the asymptotic properties of our proposed test statistic. We examine the performance of our proposed test through simulation studies in both survival and competing risks settings. The proposed test may be more powerful than tests based on the hazard function in settings where the center effect is time-varying. We illustrate the test using a multicenter registry study of survival and competing risks outcomes after hematopoietic cell transplantation.

中文翻译：

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使用伪值回归测试中心对生存和竞争风险结果的影响。


在多中心研究中，集群效应的存在会导致中心内结果之间的相关性，并且需要不同的技术来处理这种相关性。集群效应测试可以作为预筛选步骤，帮助指导研究人员进行适当的分析。根据事件时间数据，提出了评分测试，用于测试危险函数是否存在中心效应。然而，有时研究人员有兴趣直接建模其他量，例如固定时间的生存概率或累积发生率。我们提出使用伪值回归来检验是否存在直接作用于感兴趣数量的中心效应，并推导出我们提出的检验统计量的渐近属性。我们通过生存和竞争风险环境中的模拟研究来检查我们提出的测试的性能。在中心效应随时间变化的情况下，所提出的测试可能比基于危险函数的测试更强大。我们使用造血细胞移植后生存和竞争风险结果的多中心注册研究来说明该测试。