Estimation methods for time‐dependent AUC models with survival data
Estimation methods for time‐dependent AUC models with survival data
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DOI：
10.1002/cjs.10046
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发表时间：
2009-11
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影响因子：
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通讯作者：
Hung Hung-Hung;Chin‐Tsang Chiang
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文献类型：
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作者：
Hung Hung-Hung;Chin‐Tsang Chiang
用于疾病筛查的临床试验的性能通常使用受试者工作特征（ROC）曲线下面积（AUC）进行评估。最近的发展将传统的AUC设置扩展到具有二元时变失效状态的AUC。在不考虑协变量的情况下，我们的第一个主题是为时间相关的AUC提出一个简单且易于计算的非参数估计器。此外，我们使用具有时变系数的广义线性模型来表征随时间变化的AUC作为协变量值的函数。提出了相应的估计方法来估计感兴趣的参数函数。导出的极限高斯过程和估计的渐近方差使我们能够构造auc的近似置信区域。我们提出的估计器和推理程序的有限样本性质通过广泛的模拟进行了检验。对艾滋病临床试验组（ACTG） 175数据的分析进一步显示了所提出方法的适用性。加拿大统计杂志38:8-26；2010©2009加拿大统计学会
The performance of clinical tests for disease screening is often evaluated using the area under the receiver‐operating characteristic (ROC) curve (AUC). Recent developments have extended the traditional setting to the AUC with binary time‐varying failure status. Without considering covariates, our first theme is to propose a simple and easily computed nonparametric estimator for the time‐dependent AUC. Moreover, we use generalized linear models with time‐varying coefficients to characterize the time‐dependent AUC as a function of covariate values. The corresponding estimation procedures are proposed to estimate the parameter functions of interest. The derived limiting Gaussian processes and the estimated asymptotic variances enable us to construct the approximated confidence regions for the AUCs. The finite sample properties of our proposed estimators and inference procedures are examined through extensive simulations. An analysis of the AIDS Clinical Trials Group (ACTG) 175 data is further presented to show the applicability of the proposed methods. The Canadian Journal of Statistics 38:8–26; 2010 © 2009 Statistical Society of Canada