Frailties in multi-state models: Are they identifiable? Do we need them?
Frailties in multi-state models: Are they identifiable? Do we need them?
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DOI：
10.1177/0962280211424665
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发表时间：
2015-12-01
影响因子：
2.3
通讯作者：
van Houwelingen, Hans C.
中科院分区：
文献类型：
--
作者：
Putter, Hein;van Houwelingen, Hans C.
在生存模型中加入潜在的弱点有两个目的：(1)对聚集数据中的相关性进行建模；(2)解释单变量生存模型不符合的情况，如偏离比例风险假设。多态模型介于单变量数据和聚集数据之间。脆弱模型可以帮助理解顺序转变中的相关性(如在集群数据中)，并有助于解释竞争风险模型中协变量效应中的一些奇怪现象(如在单变量数据中)。脆弱模型的可能性将在乳腺癌患者的数据集上举例说明，其中死亡为吸收状态，局部复发和远处转移为中间事件。
The inclusion of latent frailties in survival models can serve two purposes: (1) the modelling of dependence in clustered data, (2) explaining lack of fit of univariate survival models, like deviation from the proportional hazards assumption. Multi-state models are somewhere between univariate data and clustered data. Frailty models can help in understanding the dependence in sequential transitions (like in clustered data) and can be useful in explaining some strange phenomena in the effect of covariates in competing risks models (like in univariate data). The (im)possibilities of frailty models will be exemplified on a data set of breast cancer patients with death as absorbing state and local recurrence and distant metastasis as intermediate events.