Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function
Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function
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DOI：
10.1111/j.0006-341x.2005.031209.x
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发表时间：
2005-03-01
期刊：
影响因子：
1.9
通讯作者：
Andersen, PK
中科院分区：
文献类型：
--
作者：
Klein, JP;Andersen, PK
通常，竞争风险结果的回归模型是基于粗风险率的比例风险模型。这些估计往往不同意的印象，从图的累积发病率函数的每一个水平的危险因素。我们提出了一种技术，直接建模的累积发病率函数。该方法基于累积发生率曲线构造的刀切统计量的伪值。这些伪值用于广义估计方程中以获得模型参数的估计。我们研究这个估计的属性，并将该技术应用于白血病骨髓移植患者的替代供体对复发的影响的研究。
Typically, regression models for competing risks outcomes are based on proportional hazards models for the crude hazard rates. These estimates often do not agree with impressions drawn from plots of cumulative incidence functions for each level of a risk factor. We present a technique which models the cumulative incidence functions directly. The method is based on the pseudovalues from a jackknife statistic constructed from the cumulative incidence curve. These pseudovalues are used in a generalized estimating equation to obtain estimates of model parameters. We study the properties of this estimator and apply the technique to a study of the effect of alternative donors on relapse for patients given a bone marrow transplant for leukemia.