Predicting Survival Probabilities with Semiparametric Transformation Models
Predicting Survival Probabilities with Semiparametric Transformation Models
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DOI：
10.1080/01621459.1997.10473620
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发表时间：
1997-03
影响因子：
3.7
通讯作者：
S. Cheng;Lee-Jen Wei;Z. Ying
中科院分区：
文献类型：
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作者：
S. Cheng;Lee-Jen Wei;Z. Ying
摘要预测未来患者的生存概率是用回归模型拟合生存数据的主要目标之一。在这篇文章中，我们考虑了一个大类的半参数转换模型，其中包括著名的比例风险和比例优势模型，故障时间数据的分析。具体来说，我们提出了逐点和同时置信区间程序的生存概率的未来患者的特定协变量。这些程序可以很容易地通过模拟实现，并说明了从两个著名的临床研究的数据。
Abstract Prediction of survival probabilities for future patients is one of the main goals of fitting survival data with regression models. In this article we consider a large class of semiparametric transformation models, which includes the well-known proportional hazards and proportional odds models, for the analysis of failure time data. Specifically, we propose pointwise and simultaneous confidence interval procedures for the survival probability of future patients with specific covariates. These procedures can be easily implemented through simulation and are illustrated with the data from two well-known clinical studies.