Inference on the symmetry point-based optimal cut-off point and associated sensitivity and specifcity with application to SARS-CoV-2 antibody data

Franco Pereira, Alba María; Pardo Llorente, M. Del Carmen; Nakas, C.T.; Reiser, B.

Inference on the symmetry point-based optimal cut-off point and associated sensitivity and specifcity with application to SARS-CoV-2 antibody data

Publication date

2023

Authors

Franco Pereira, Alba María

Pardo Llorente, M. Del Carmen

Nakas, C.T.

Reiser, B.

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URI

https://hdl.handle.net/20.500.14352/87323

Abstract

In the presence of a continuous response test/biomarker, it is often necessary to identify a cut-off point value to aid binary classification between diseased and non-diseased subjects. The symmetry-point approach which maximizes simultaneously both types of correct classification is one way to determine an optimal cut-off point. In this article, we study methods for constructing confidence intervals independently for the symmetry point and its corresponding sensitivity, as well as respective joint nonparametric confidence regions. We illustrate using data on the generation of antibodies elicited two weeks post-injection after the second dose of the Pfizer/BioNTech vaccine in adult healthcare workers.

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Biomatemáticas

Unesco subjects

2404 Biomatemáticas

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