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Semiparametic models and estimation procedures for binormal ROC curves with multiple biomarkers

机译:具有多个生物标志物的双正态ROC曲线的半参数模型和估计程序

摘要

In diagnostic medicine, there is great interest in developing strategies for combining biomarkers in order to optimize classification accuracy. A popular model that has been used for receiver operating characteristic (ROC) curve modelling when one biomarker is available is the binormal model. Extension of the model to accommodate multiple biomarkers has not been considered in this literature. Here, we consider a multivariate binormal framework for combining biomarkers using copula functions that leads to a natural multivariate extension of the binormal model. Estimation in this model will be done using rank-based procedures. We show that the Van der Waerden rank score coefficient estimation procedure can be used for the multivariate binormal model. We also discuss adjustment for covariates in this class of models. We provide a simple two-stage estimation procedure that can be fit using standard software packages. Asymptotic results of the proposed methods are given. The techniques are applied to data from two cancer biomarker studies.
机译:在诊断医学中,对开发组合生物标记以优化分类准确性的策略引起了极大兴趣。双标准模型是一种流行的模型,当一种生物标记可用时,该模型已用于接收器工作特性(ROC)曲线建模。该文献未考虑扩展模型以适应多种生物标志物。在这里,我们考虑使用copula函数组合生物标记的多元双正态框架,该框架导致双正态模型的自然多元扩展。该模型中的估计将使用基于等级的过程来完成。我们表明范德华登等级评分系数估计程序可用于多元双正态模型。我们还将讨论此类模型中协变量的调整。我们提供了一个简单的两阶段估算程序,可以使用标准软件包进行拟合。给出了所提出方法的渐近结果。该技术已应用于两项癌症生物标志物研究的数据。

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  • 作者

    Ghosh Debashis;

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  • 年度 2004
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