半参数混合曲线模型估计的预光滑方法
A presmoothing approach for estimation in semiparametric mixture cure models
摘要：
处理生存分析数据时的一个挑战是解释治愈分数，这意味着一些受试者将永远不会经历感兴趣的事件。混合治愈模型经常用于估计易感受试者的治愈概率和至事件发生时间，通常假设发生率为参数（logistic）形式。我们提出了一个新的估计过程的参数治愈率依赖于一个初步的平滑估计，是独立的模型假设的延迟。我们调查的估计量的理论性质，并通过模拟表明，在logistic/Cox模型，premoothing导致更准确的结果相比，极大似然估计。为了说明实际使用，我们应用新的估计程序的两项研究黑色素瘤生存数据。
英文摘要：
A challenge when dealing with survival analysis data is accounting for a cure fraction, meaning that some subjects will never experience the event of interest. Mixture cure models have been frequently used to estimate both the probability of being cured and the time to event for the susceptible subjects, by usually assuming a parametric (logistic) form of the incidence. We propose a new estimation procedure for a parametric cure rate that relies on a preliminary smooth estimator and is independent of the model assumed for the latency. We investigate the theoretical properties of the estimators and show through simulations that, in the logistic/Cox model, presmoothing leads to more accurate results compared to the maximum likelihood estimator. To illustrate the practical use, we apply the new estimation procedure to two studies of melanoma survival data.
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