Estimating the area under a receiver operating characteristic curve using partially ordered sets.
imperfect ranking
isotonic estimation
maximum likelihood
nonparametric estimation
relative efficiency
tie information
Journal
The international journal of biostatistics
ISSN: 1557-4679
Titre abrégé: Int J Biostat
Pays: Germany
ID NLM: 101313850
Informations de publication
Date de publication:
07 08 2020
07 08 2020
Historique:
received:
29
10
2019
accepted:
08
06
2020
pubmed:
9
8
2020
medline:
15
12
2021
entrez:
9
8
2020
Statut:
epublish
Résumé
Ranked set sampling (RSS), known as a cost-effective sampling technique, requires that the ranker gives a complete ranking of the units in each set. Frey (2012) proposed a modification of RSS based on partially ordered sets, referred to as RSS-t in this paper, to allow the ranker to declare ties as much as he/she wishes. We consider the problem of estimating the area under a receiver operating characteristics (ROC) curve using RSS-t samples. The area under the ROC curve (AUC) is commonly used as a measure for the effectiveness of diagnostic markers. We develop six nonparametric estimators of the AUC with/without utilizing tie information based on different approaches. We then compare the estimators using a Monte Carlo simulation and an empirical study with real data from the National Health and Nutrition Examination Survey. The results show that utilizing tie information increases the efficiency of estimating the AUC. Suggestions about when to choose which estimator are also made available to practitioners.
Identifiants
pubmed: 32764163
doi: 10.1515/ijb-2019-0127
pii: /j/ijb.ahead-of-print/ijb-2019-0127/ijb-2019-0127.xml
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
139-152Subventions
Organisme : NIGMS NIH HHS
ID : R15 GM131390
Pays : United States
Informations de copyright
© 2020 Walter de Gruyter GmbH, Berlin/Boston.
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