论文标题
协变量调整后的ROC曲线的估计量缺失生物标志物值
Estimators for covariate-adjusted ROC curves with missing biomarkers values
论文作者
论文摘要
在本文中，当生物标志物之间出现缺失的观察结果时，我们会提出ROC曲线的三个估计器。其中两个过程假设我们有协变量，可以使用反概率加权方法或IT平滑版本来估计倾向和估计器。另一个假设协变量通过回归模型与生物标志物相关，该模型使我们能够构建基于卷积的分布和分位功能的估计值。在轻度条件下获得一致性结果。通过数值研究，我们评估了不同建议的有限样本性能。还分析了真实的数据集。
In this paper, we present three estimators of the ROC curve when missing observations arise among the biomarkers. Two of the procedures assume that we have covariates that allow to estimate the propensity and the estimators are obtained using an inverse probability weighting method or a smoothed version of it. The other one assumes that the covariates are related to the biomarkers through a regression model which enables us to construct convolution--based estimators of the distribution and quantile functions. Consistency results are obtained under mild conditions. Through a numerical study we evaluate the finite sample performance of the different proposals. A real data set is also analysed.
