Joint Modelling of Repeated Measures and Survival Time Data
Joint Modelling of Repeated Measures and Survival Time Data
复制标题
重复测量和生存时间数据的联合建模
DOI：
10.1002/bimj.200390039
复制
发表时间：
2003
影响因子：
1.7
通讯作者：
Youngjo Lee
中科院分区：
文献类型：
--
作者：
I. Ha;T. Park;Youngjo Lee
在许多临床试验中，重复测量数据和事件历史数据同时从同一受试者中观察到。这两种类型的反应通常是相关的，因为它们来自同一个主题。在本文中，我们提出了一个联合模型的重复测量数据和事件历史数据的组合分析的层次广义线性模型的框架。重复测量和事件时间之间的相关性是通过引入共享的随机效应来建模的。使用分层似然法估计模型参数。所提出的模型说明使用一个真实的数据集的肾移植患者。
In many clinical trials both repeated measures data and event history data are simultaneously observed from the same subject. These two types of responses are usually correlated, because they are from the same subject. In this article, we propose a joint model for the combined analysis of repeated measures data and event history data in the framework of hierarchical generalized linear models. The correlation between repeated measures and event time is modelled by introducing a shared random effect. The model parameters are estimated using the hierarchical‐likelihood approach. The proposed model is illustrated using a real data set for the renal transplant patients.
影响因子：
1.9
作者：
DEGRUTTOLA, V;TU, XM
通讯作者：
TU, XM