Verification bias is a well-known problem that may occur in the evaluation of predictive ability of diagnostic tests. When a binary disease status is considered, various solutions can be found in the literature to cor- rect inference based on usual measures of test accuracy, such as the receiver operating characteristic (ROC) curve or the area underneath. Evaluation of the predictive ability of continuous diagnostic tests in the presence of ver- ification bias for an ordinal three-class disease status is here discussed. In particular, several verification bias-corrected estimators of the ROC surface and of the volume underneath are proposed. Consistency and asymptotic normality of the proposed estimators are established and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations are also given.
To Duc Khanh, Chiogna Monica, Adimari Gianfranco (2016). Bias–corrected methods for estimating the receiver operating characteristic surface of continuous diagnostic tests. ELECTRONIC JOURNAL OF STATISTICS, 10(2), 3063-3113 [10.1214/16-EJS1202].
Bias–corrected methods for estimating the receiver operating characteristic surface of continuous diagnostic tests
Chiogna Monica;
2016
Abstract
Verification bias is a well-known problem that may occur in the evaluation of predictive ability of diagnostic tests. When a binary disease status is considered, various solutions can be found in the literature to cor- rect inference based on usual measures of test accuracy, such as the receiver operating characteristic (ROC) curve or the area underneath. Evaluation of the predictive ability of continuous diagnostic tests in the presence of ver- ification bias for an ordinal three-class disease status is here discussed. In particular, several verification bias-corrected estimators of the ROC surface and of the volume underneath are proposed. Consistency and asymptotic normality of the proposed estimators are established and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations are also given.File | Dimensione | Formato | |
---|---|---|---|
16-EJS1202-1.pdf
accesso aperto
Tipo:
Versione (PDF) editoriale
Licenza:
Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione
1.95 MB
Formato
Adobe PDF
|
1.95 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.