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The exponentiated exponential mixture and non-mixture cure rate model in the presence of covariates

机译:协变量存在下的指数指数混合和非混合硫化率模型

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This paper presents estimates for the parameters included in long-term mixture and non-mixture lifetime models, applied to analyze survival data when some individuals may never experience the event of interest. We consider the case where the lifetime data have a two-parameters exponentiated exponential distribution. The two-parameter exponentiated exponential or the generalized exponential distribution is a particular member of the exponentiated Weibull distribution introduced by [31]. Classical and Bayesian procedures are used to get point and confidence intervals of the unknown parameters. We consider a general survival model where the scale, shape and cured fraction parameters of the exponentiated exponential distribution depends on covariates.
机译:本文介绍了长期混合和非混合寿命模型中包含的参数估计值,这些估计值用于在某些人可能从未经历过所关注事件时分析生存数据。我们考虑寿命数据具有两个参数的指数分布的情况。两参数指数化指数分布或广义指数分布是[31]引入的指数化威布尔分布的特定成员。经典和贝叶斯程序用于获取未知参数的点和置信区间。我们考虑一个通用的生存模型,其中指数幂分布的规模,形状和固化分数参数取决于协变量。

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