Nonparametric Estimation of ROC Surfaces Under Verification Bias

Autor:	Khanh To Duc, Monica Chiogna, Gianfranco Adimari
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	diagnostic tests missing at random true class fractions nearest neighbor imputation Statistics HA1-4737 Probabilities. Mathematical statistics QA273-280
Zdroj:	Revstat Statistical Journal, Vol 18, Iss 5 (2020)
Druh dokumentu:	article
ISSN:	1645-6726 2183-0371
DOI:	10.57805/revstat.v18i5.327
Popis:	Verification bias is a well known problem that can affect the statistical evaluation of the predictive ability of a diagnostic test when the true disease status is unknown for some of the patients under study. In this paper, we deal with the assessment of continuous diagnostic tests when an (ordinal) three-class disease status is considered and propose a fully nonparametric verification bias-corrected estimator of the ROC surface based on nearest-neighbor imputation. Consistency and asymptotic normality of the proposed estimator are proved under the missing at random assumption, and its finite sample behavior is investigated by means of Monte Carlo experiments. Variance estimation is also discussed and an illustrative example is presented.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/f3dfb98a9ffb4376b225a98c2b67b854 Zobrazit plný text záznamu View record in DOAJ