Capturing simple and complex time-dependent effects using flexible parametric survival models: A simulation study
Capturing simple and complex time-dependent effects using flexible parametric survival models: A simulation study
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DOI：
10.1080/03610918.2019.1634201
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发表时间：
2019-07-05
影响因子：
0.9
通讯作者：
Lambert, Paul C.
中科院分区：
文献类型：
--
作者：
Bower, Hannah;Crowther, Michael J.;Lambert, Paul C.
非比例风险在至事件发生时间数据中很常见，可以在灵活的参数生存模型中使用受限三次样条进行建模。这项模拟研究评估了这些模型捕获非比例风险的能力，以及赤池信息准则（AIC）和贝叶斯信息准则（BIC）选择自由度的能力。不同复杂性情景的模拟结果表明，简单情景的生存和风险函数几乎没有偏差;当模拟的自由度较少时，复杂情景的偏差会增加。无论是AIC还是BIC都没有表现得更好，而且这两种模型都没有什么偏差。
Non-proportional hazards are common within time-to-event data and can be modeled using restricted cubic splines in flexible parametric survival models. This simulation study assesses the ability of these models in capturing non-proportional hazards, and the ability of the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) in selecting degrees of freedom. The simulation results for scenarios with differing complexities showed little bias in the survival and hazard functions for simple scenarios; bias increased in complex scenarios when fewer degrees of freedom were modeled. Neither AIC nor BIC consistently performed better and both generally selected models with little bias.