Recurrent events analysis in the presence of time-dependent covariates and dependent censoring
Recurrent events analysis in the presence of time-dependent covariates and dependent censoring
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DOI：
10.1111/j.1467-9868.2004.00442.x
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发表时间：
2004-01-01
影响因子：
5.8
通讯作者：
Butler, S
中科院分区：
文献类型：
--
作者：
Miloslavsky, M;Keles, S;Butler, S
最近，循环事件模型受到了相当大的关注。大多数方法显示了参数估计值的一致性，假设是删失独立于模型中包含的协变量条件下关注的复发事件过程。我们提供了一个可用的复发事件分析方法的概述，并提出了一个逆概率截尾加权估计的回归参数的Andersen-Gill模型，通常用于复发事件分析。如果一致地估计删失机制，则该估计量在信息删失下保持一致，并且在独立删失的情况下，它通常改进了Andersen-Gill模型的朴素估计量。我们通过模拟研究说明了在信息删失的情况下特设估计量的偏倚，并提供了囊性纤维化患者在某些患者失访时复发性肺加重的数据分析。
Recurrent events models have had considerable attention recently. The majority of approaches show the consistency of parameter estimates under the assumption that censoring is independent of the recurrent events process of interest conditional on the covariates that are included in the model. We provide an overview of available recurrent events analysis methods and present an inverse probability of censoring weighted estimator for the regression parameters in the Andersen-Gill model that is commonly used for recurrent event analysis. This estimator remains consistent under informative censoring if the censoring mechanism is estimated consistently, and it generally improves on the naive estimator for the Andersen-Gill model in the case of independent censoring. We illustrate the bias of ad hoc estimators in the presence of informative censoring with a simulation study and provide a data analysis of recurrent lung exacerbations in cystic fibrosis patients when some patients are lost to follow-up.