The existence of items not susceptible to the event of interest is of both theoretical and practical importance. Although researchers may provide, for example, biological, medical, or sociological evidence for the presence of such items (cured), statistical models performing well under the existence or not of a cured proportion, frequently offer a necessary flexibility. This work introduces a new reparameterization of a flexible family of cure models, which not only includes among its special cases, the most studied cure models (such as the mixture, bounded cumulative hazard, and negative binomial cure model) but also classical survival models (ie, without cured items). One of the main properties of the proposed family, apart from its computationally tractable closed form, is that the case of zero cured proportion is not found at the boundary of the parameter space, as it typically happens to other families. A simulation study examines the (finite) performance of the suggested methodology, focusing to the estimation through EM algorithm and model discrimination, by the aid of the likelihood ratio test and Akaike information criterion; for illustrative purposes, analysis of two real life datasets (on recidivism and cutaneous melanoma) is also carried out.

中文翻译：

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关于灵活的固化模型族的重新参数化

不易受感兴趣事件影响的项目的存在具有理论和实践意义。尽管研究人员可以提供例如生物、医学或社会学证据证明这些物品（治愈）的存在，但统计模型在治愈或不治愈的情况下表现良好，通常提供必要的灵活性。这项工作引入了灵活的治愈模型族的新重新参数化，其中不仅包括在其特殊情况下研究最多的治愈模型（如混合、有界累积风险和负二项式治愈模型），还包括经典生存模型（即，没有固化的物品）。提议的家庭的主要属性之一，除了其计算上易于处理的封闭形式，是在参数空间的边界处没有发现零固化比例的情况，因为它通常发生在其他族中。一项模拟研究检查了所建议方法的（有限）性能，重点是借助似然比检验和 Akaike 信息准则通过 EM 算法和模型判别进行估计；出于说明目的，还对两个现实生活中的数据集（关于累犯和皮肤黑色素瘤）进行了分析。