Bantis Leonidas E, Tsimikas John V, Georgiou Stelios D
Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, Samos 83200, Greece.
Biom J. 2013 Sep;55(5):719-40. doi: 10.1002/bimj.201200158. Epub 2013 Apr 3.
The use of ROC curves in evaluating a continuous or ordinal biomarker for the discrimination of two populations is commonplace. However, in many settings, marker measurements above or below a certain value cannot be obtained. In this paper, we study the construction of a smooth ROC curve (or surface in the case of three populations) when there is a lower or upper limit of detection. We propose the use of spline models that incorporate monotonicity constraints for the cumulative hazard function of the marker distribution. The proposed technique is computationally stable and simulation results showed a satisfactory performance. Other observed covariates can be also accommodated by this spline-based approach.
在评估用于区分两个群体的连续或有序生物标志物时，使用ROC曲线是很常见的。然而，在许多情况下，无法获得高于或低于某个值的标志物测量值。在本文中，我们研究了在存在检测下限或上限的情况下，如何构建平滑的ROC曲线（对于三个群体的情况则是曲面）。我们建议使用对标志物分布的累积风险函数纳入单调性约束的样条模型。所提出的技术在计算上是稳定的，模拟结果显示出令人满意的性能。这种基于样条的方法也可以纳入其他观察到的协变量。
