A nonparametric mixture model for cure rate estimation
A nonparametric mixture model for cure rate estimation
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DOI：
10.1111/j.0006-341x.2000.00237.x
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发表时间：
2000-03-01
期刊：
影响因子：
1.9
通讯作者：
Dear, KBG
中科院分区：
文献类型：
--
作者：
Peng, YW;Dear, KBG
与参数方法相比，非参数方法在治愈率分析中受到的关注较少。本文研究了一种一般的非参数混合模型。采用比例风险假设来模拟协变量对未治愈患者失效时间的影响。采用Ehl算法、边际似然法和多重插值来估计模型中感兴趣的参数。该模型扩展了其他研究人员提出的模型并改进了估计方法。它还扩展了Cox的比例风险回归模型，允许一定比例的无事件患者，并调查该比例的协变量效应。通过仿真研究了该模型及其估计方法。对乳腺癌数据的应用，包括与其他研究人员先前使用参数模型和现有非参数模型的分析进行比较，证实了参数模型的结论，而不是现有非参数模型的结论。
Nonparametric methods have attracted less attention than their parametric counterparts for cure rate analysis. In this paper, we study a general nonparametric mixture model. The proportional hazards assumption is employed in modeling the effect of covariates on the failure time of patients who are not cured. The Ehl algorithm, the marginal likelihood approach, and multiple imputations are employed to estimate parameters of interest in the model. This model extends models and improves estimation methods proposed by other researchers. It also extends Cox's proportional hazards regression model by allowing a proportion of event-free patients and investigating covariate effects on that proportion. The model and its estimation method are investigated by simulations. An application to breast cancer data, including comparisons with previous analyses using a parametric model and an existing nonparametric model by other researchers, confirms the conclusions from the parametric model but not those from the existing nonparametric model.