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A procedure for determining whether a simple combination of diagnostic tests may be noninferior to the theoretical optimum combination.

机译:一种确定诊断测试的简单组合是否可能不逊于理论上最佳组合的过程。

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摘要

Diagnosis accuracy can be improved by combining several complementary diagnostic tests. The likelihood ratio (LR) function is the optimal combination because it achieves the largest area under the receiver operating characteristic (ROC) curve. Derivation and interpretation of the LR function, however, can be complicated. Linear discriminant/logistic functions are simple but may not be optimal. In this article, the authors propose a statistical framework to determine when such linear combinations are noninferior alternatives to the LR function. They propose a nonparametric procedure to calculate LR functions and estimate the optimal area under the curve (AUC). The authors then define noninferiority of a simpler combination to the LR function with regard to the AUC of ROC curves. A bootstrap procedure is proposed to test the noninferiority. Monte Carlo simulation experiments are used to evaluate the performance of the proposed methods. Data from the Study of Osteoporotic Fractures are used to demonstrate the procedure.
机译:通过组合几个补充的诊断测试可以提高诊断准确性。似然比(LR)功能是最佳组合,因为它可以在接收器工作特性(ROC)曲线下实现最大面积。但是,LR函数的推导和解释可能很复杂。线性判别/逻辑函数很简单,但可能不是最佳的。在本文中,作者提出了一个统计框架,以确定何时这些线性组合是LR函数的非劣等选择。他们提出了一种非参数程序来计算LR函数并估计曲线下的最佳面积(AUC)。然后作者就ROC曲线的AUC定义了与LR函数相比更简单的组合的不劣性。提出了引导程序以测试非劣势性。蒙特卡罗模拟实验用于评估所提出方法的性能。骨质疏松性骨折研究的数据用于证明该程序。

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