2026-06-28T10:11:35Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/873232023-08-11T07:42:40Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense
author
Franco Pereira, Alba María
author
Pardo Llorente, M. Del Carmen
author
Nakas, C.T.
author
Reiser, B.
2023-07-24T12:02:13Z
2023-07-24T12:02:13Z
2023
10.57645/20.8080.02.5
https://hdl.handle.net/20.500.14352/87323
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.
eng
Inference on the symmetry point-based optimal cut-off point and associated sensitivity and specifcity with application to SARS-CoV-2 antibody data
journal article
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URL
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File
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6a83a9f021d6643c865f32fa06245d25
1036712
application/pdf
franco-pereira-inference.pdf