We propose new methods that provide approximate joint confidence regions for the optimal sensitivity and specificity of a diagnostic test, fixed by the Youden index criterion. Such methods are semiparametric and overcome limitations of alternative approaches available in the literature. Our proposal is based on empirical likelihood pivots and covers two situations: binormal model and binormal model after the use of Box-Cox transformations. In the last case, we show how to use two different transformations, for the healthy and the diseased subjects.

Confidence regions for optimal sensitivity and specificity of a diagnostic test

Gianfranco Adimari;Duc-Khanh To
;
Monica Chiogna
2022

Abstract

We propose new methods that provide approximate joint confidence regions for the optimal sensitivity and specificity of a diagnostic test, fixed by the Youden index criterion. Such methods are semiparametric and overcome limitations of alternative approaches available in the literature. Our proposal is based on empirical likelihood pivots and covers two situations: binormal model and binormal model after the use of Box-Cox transformations. In the last case, we show how to use two different transformations, for the healthy and the diseased subjects.
2022
Book of Short Papers SIS 2022
9788891932310
File in questo prodotto:
File Dimensione Formato  
Khanh_Adimari_Monica_SIS_2022.pdf

accesso aperto

Tipologia: Published (publisher's version)
Licenza: Accesso gratuito
Dimensione 140.32 kB
Formato Adobe PDF
140.32 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3455373
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact