Tree-structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria
Tree-structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria
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DOI：
10.1007/s11222-005-1311-z
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发表时间：
2005-07-01
影响因子：
2.2
通讯作者：
Boivin, JF
中科院分区：
文献类型：
--
作者：
Negassa, A;Ciampi, A;Boivin, JF
在树结构子群分析的背景下，计算成本低廉的模型选择标准的性能进行了研究。它通过模拟表明，没有一个单一的模型选择标准表现出一致的上级性能在广泛的情况下。因此，提出了一种两阶段的模型选择方法，并取得了令人满意的效果.给出了子群分析的应用实例。讨论了与树结构子群分析相关的问题，并提出了实用的解决方案.
The performance of computationally inexpensive model selection criteria in the context of tree-structured subgroup analysis is investigated. It is shown through simulation that no single model selection criterion exhibits a uniformly superior performance over a wide range of scenarios. Therefore, a two- stage approach for model selection is proposed and shown to perform satisfactorily. Applied example of subgroup analysis is presented. Problems associated with tree- structured subgroup analysis are discussed and practical solutions are suggested.