Application of empirical Bayes inference to estimation of rate of change in the presence of informative right censoring.
Application of empirical Bayes inference to estimation of rate of change in the presence of informative right censoring.
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DOI：
10.1002/sim.4780110507
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发表时间：
1992
影响因子：
2
通讯作者：
M. Mori;G. Woodworth;R. Woolson
中科院分区：
文献类型：
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作者：
M. Mori;G. Woodworth;R. Woolson
我们应用莫里斯的参数经验贝叶斯推断来估计不完整纵向研究的变化率，其中正确的审查过程被认为是信息丰富的，也就是说，受试者参与研究的时间长度与研究变量的水平相关。忽略这种关联可能会导致对变化率的估计有偏差。所提出的方法提供了个体受试者以及整个组的变化率的估计，并根据信息右审查进行了调整。该方法被认为比基于特定的审查分布参数模型的方法更稳健。在非信息性右审查下，这些斜率估计量相当于 Fearn 导出的贝叶斯估计量。我们通过涉及肾移植数据的示例来说明该方法。我们通过模拟研究评估该方法的性能。
We apply parametric empirical Bayes inference of Morris to the estimation of rate of change from incomplete longitudinal studies where the right censoring process is considered informative, that is, the length of time the subjects participate in the study is associated with level of the study variable. Ignoring such an association can result in a biased estimate of rate of change. The proposed method provides estimates of rate of change for individual subjects as well as for the entire group, adjusted for informative right censoring. The method is considered more robust than those based on a specific parametric model for the censoring distribution. Under non-informative right censoring these estimators of slopes are equivalent to the Bayes estimators derived by Fearn. We illustrate the method with an example involving renal transplant data. We evaluate the method's performance through a simulation study.