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TESTS FOR CURED PROPORTION FOR RECURRENT EVENT COUNT DATA WHEN THE DATA ARE CENSORED

机译:在检查数据后对递归事件计数数据的按比例进行测试

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摘要

Sumathi and Rao (2008) proposed a cure model for recurrent event count data. The proposed model was based on the zero inflated Poisson (ZIP) distribution. Several tests were proposed for testing the cured proportion when the data set is uncensored (Sumathi and Rao, 2010). But in long term follow up studies, the investigators very often come across situations where the patients are lost to follow up and the data sets are said to be censored. The present paper is an extension of the work of Sumathi and Rao (2010). In the present paper, tests are proposed for testing the cured proportion in a randomly censored recurrent event count data. The small sample performances of the proposed tests are studied using simulations.
机译:Sumathi和Rao(2008)提出了针对复发事件计数数据的治愈模型。所提出的模型基于零膨胀泊松(ZIP)分布。当数据集未经审查时,提出了一些测试来测试固化比例(Sumathi and Rao,2010)。但是在长期的随访研究中,研究人员经常会遇到患者失访的情况,并且数据集被审查。本文是Sumathi和Rao(2010)的工作的延伸。在本文中,提出了用于在随机检查的复发事件计数数据中测试治愈比例的测试。建议的测试的小样本性能使用模拟进行研究。

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