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Modeling heterogeneity for bivariate survival data by the compound Poisson distribution with random scale

机译:通过具有随机尺度的复合泊松分布为双变量生存数据建模异质性

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摘要

We propose a bivariate Weibull regression model with heterogeneity (frailty or random effect) which is generated by compound Poisson distribution with random scale. We assume that the bivariate survival data follow bivariate Weibull of Hanagal (2004). There are some interesting situations like survival times in genetic epidemiology, dental implants of patients and twin births (both monozygotic and dizygotic) where genetic behavior (which is unknown and random) of patients follows a known frailty distribution. These are the situations which motivate us to study this particular model. We propose a two stage maximum likelihood estimation procedure for the parameters in the proposed model and develop large sample tests for testing significance of regression parameters.
机译:我们提出了具有异质性(脆弱或随机效应)的双变量Weibull回归模型,该模型由具有随机规模的复合Poisson分布生成。我们假设双变量生存数据遵循Hanagal(2004)的双变量Weibull。有一些有趣的情况,例如遗传流行病学中的生存时间,患者的牙齿植入物和双胎(单卵和双卵),其中患者的遗传行为(未知和随机)遵循已知的脆弱分布。这些情况促使我们研究此特定模型。我们针对所提出的模型中的参数提出了两阶段最大似然估计程序,并开发了大样本测试来测试回归参数的重要性。

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