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

A. M. Franco-Pereira, M. C. Pardo, C. T. Nakas, B. Reiser

Research output: Contribution to journalArticlepeer-review

Abstract

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

Original languageEnglish
Pages (from-to)187-203
Number of pages17
JournalSORT
Volume47
Issue number1
DOIs
StatePublished - 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Institut d'Estadistica de Catalunya. All rights reserved.

Keywords

  • Box-Cox transformation
  • Confdence regions
  • Empirical chi-square function
  • Empirical likelihood function
  • Sensitivity
  • Specifcity.

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research

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