Inference on the symmetry point-based optimal cut-off point and associated sensitivity and specificity with application to SARS-CoV-2 antibody data
Franco-Pereira, Alba María (Complutense University of Madrid)
Pardo Llorente, M. Carmen (Complutense University of Madrid)
Nakas, Christos T. (University of Thessaly (Grècia). University of Bern (Suïssa))
Reiser, Benjamin (University of Haifa)

Date:	2023
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.
Note:	Acknowledgments. This work was supported by grants PID2019-104681RB-I00. Data courtesy of Dr Konstantina Kontopoulou.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Empirical likelihood function ; Empirical chi-square function ; Box-Cox transformation ; Confidence regions ; Sensitivity ; Specificity
Published in:	SORT : statistics and operations research transactions, Vol. 47 Núm. 1 (2023) , p. 187-204, ISSN 2013-8830

Adreça original: https://raco.cat/index.php/SORT/article/view/416954
DOI: 10.57645/20.8080.02.5

18 p, 1.0 MB

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