Please use this identifier to cite or link to this item:
http://hdl.handle.net/11452/34626
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.date.accessioned | 2023-10-27T10:34:36Z | - |
dc.date.available | 2023-10-27T10:34:36Z | - |
dc.date.issued | 2017-08-17 | - |
dc.identifier.citation | Sığırlı, D. vd. (2018). ''Adaptation of the weighted Kaplan-Meier method to time-dependent ROC curves''. Journal of the National Science Foundation of Sri Lanka, 46(1), 11-21. | en_US |
dc.identifier.issn | 1391-4588 | - |
dc.identifier.issn | 2362-0161 | - |
dc.identifier.uri | https://doi.org/10.4038/jnsfsr.v46i1.8261 | - |
dc.identifier.uri | https://jnsfsl.sljol.info/articles/10.4038/jnsfsr.v46i1.8261 | - |
dc.identifier.uri | http://hdl.handle.net/11452/34626 | - |
dc.description.abstract | This study was aimed at adapting the weighted Kaplan-Meier method to time-dependent ROC curve analysis. The performances of these two time-dependent ROC curve methods were compared, in which the Kaplan-Meier estimator and weighted Kaplan-Meier estimator were used. An application was presented for pancreatic cancer patients to evaluate the prognostic ability of the CA19-9 antigen. A simulation study was performed for different scenarios to see the performance of the proposed method. In all situations, it is observed that the AUC values that were obtained by the weighted time-dependent ROC (WTDR) curves more closely approximated the real AUC values than the classical time-dependent ROC (TDR) curve method and has got smaller mean square error rates. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Natl Science Foundation | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.rights | Atıf Gayri Ticari Türetilemez 4.0 Uluslararası | tr_TR |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Science & technology - other topics | en_US |
dc.subject | Censored data | en_US |
dc.subject | Time-dependent ROC curves | en_US |
dc.subject | Weighted Kaplan-Meier | en_US |
dc.subject | Operating characteristic curves | en_US |
dc.subject | Nonparametric-estimation | en_US |
dc.subject | Survival | en_US |
dc.subject | Markers | en_US |
dc.subject | Prediction | en_US |
dc.subject | Models | en_US |
dc.title | Adaptation of the weighted Kaplan-Meier method to time-dependent ROC curves | en_US |
dc.type | Article | en_US |
dc.identifier.wos | 000429325900003 | tr_TR |
dc.identifier.scopus | 2-s2.0-85044951989 | tr_TR |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | tr_TR |
dc.contributor.department | Uludağ Üniversitesi/Tıp Fakültesi/Biyoistatistik Anabilim Dalı. | tr_TR |
dc.contributor.department | Uludağ Üniversitesi/Tıp Fakültesi/Genel Cerrahi Anabilim Dalı. | tr_TR |
dc.contributor.orcid | 0000-0002-4736-1634 | tr_TR |
dc.contributor.orcid | 0000-0002-9562-4195 | tr_TR |
dc.identifier.startpage | 11 | tr_TR |
dc.identifier.endpage | 21 | tr_TR |
dc.identifier.volume | 46 | tr_TR |
dc.identifier.issue | 1 | tr_TR |
dc.relation.journal | Journal of the National Science Foundation of Sri Lanka | en_US |
dc.contributor.buuauthor | Sığırlı, Deniz | - |
dc.contributor.buuauthor | Ercan, İlker | - |
dc.contributor.buuauthor | Balçın, Özkan | - |
dc.contributor.buuauthor | Kaya, Ekrem | - |
dc.contributor.researcherid | ABF-2367-2020 | tr_TR |
dc.contributor.researcherid | AHB-4845-2022 | tr_TR |
dc.contributor.researcherid | AAG-7319-2021 | tr_TR |
dc.contributor.researcherid | AAA-7472-2021 | tr_TR |
dc.subject.wos | Multidisciplinary sciences | en_US |
dc.indexed.wos | SCIE | en_US |
dc.indexed.scopus | Scopus | en_US |
dc.wos.quartile | Q4 | en_US |
dc.contributor.scopusid | 24482063400 | tr_TR |
dc.contributor.scopusid | 6603789069 | tr_TR |
dc.contributor.scopusid | 57189756976 | tr_TR |
dc.contributor.scopusid | 7004568109 | tr_TR |
dc.subject.scopus | Nomograms; Receiver Operating Characteristic; Prediction Model | en_US |
Appears in Collections: | Scopus Web of Science |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Deniz_vd_2018.pdf | 763.87 kB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License