Simultaneous inference for partial areas under receiver operating curves -- with a view towards efficiency

2021/04/19 by Maximilian Wechsung, Frank Konietschke, Wechsung, Maximilian +1
Mathematics · #FOS: Mathematics #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistical Methods in Clinical Trials #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.2104.09401

openalex publication_date 2021/04/19 · openalex created_date 2022/07/25 · openalex updated_date 2026/08/01

Abstract

We propose new simultaneous inference methods for diagnostic trials with elaborate factorial designs. Instead of the commonly used total area under the receiver operating characteristic (ROC) curve, our parameters of interest are partial areas under ROC curve segments that represent clinically relevant biomarker cut-off values. We construct a nonparametric multiple contrast test for these parameters and show that it asymptotically controls the family-wise type one error rate. Finite sample properties of this test are investigated in a series of computer experiments. We provide empirical and theoretical evidence supporting the conjecture that statistical inference about partial areas under ROC curves is more efficient than inference about the total areas.

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