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題名 Analysis of receiver operating characteristic curves for cure survival data and mismeasured biomarkers
作者 陳立榜
Chen, Li-Pang
貢獻者 統計系
關鍵詞 area under curve; bias correction; cure; censoring; EM algorithm; incomplete response; insertion method; mismeasurement
日期 2025-01
上傳時間 21-Aug-2025 09:33:11 (UTC+8)
摘要 Cure models and receiver operating characteristic (ROC) curve estimation are two important issues in survival analysis and have received attention for many years. In the development of biostatistics, these two topics have been well discussed separately. However, a rare development in the estimation of the ROC curve has been made available based on survival data with the cure fraction. On the other hand, while a large body of estimation methods have been proposed, they rely on an implicit assumption that the variables are precisely measured. In applications, measurement errors are generally ubiquitous and ignoring measurement errors can cause unexpected bias for the estimator and lead to the wrong conclusion. In this paper, we study the estimation of the ROC curve and the area under curve (AUC) when variables or biomarkers are subject to measurement error. We propose a valid procedure to handle measurement error effects and estimate the parameters in the cure model, as well as the AUC. We also make an effort to establish the theoretical properties with rigorous justification.
關聯 Mathematics, Vol.13, No.3, 424
資料類型 article
DOI https://doi.org/10.3390/math13030424
dc.contributor 統計系
dc.creator (作者) 陳立榜
dc.creator (作者) Chen, Li-Pang
dc.date (日期) 2025-01
dc.date.accessioned 21-Aug-2025 09:33:11 (UTC+8)-
dc.date.available 21-Aug-2025 09:33:11 (UTC+8)-
dc.date.issued (上傳時間) 21-Aug-2025 09:33:11 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158843-
dc.description.abstract (摘要) Cure models and receiver operating characteristic (ROC) curve estimation are two important issues in survival analysis and have received attention for many years. In the development of biostatistics, these two topics have been well discussed separately. However, a rare development in the estimation of the ROC curve has been made available based on survival data with the cure fraction. On the other hand, while a large body of estimation methods have been proposed, they rely on an implicit assumption that the variables are precisely measured. In applications, measurement errors are generally ubiquitous and ignoring measurement errors can cause unexpected bias for the estimator and lead to the wrong conclusion. In this paper, we study the estimation of the ROC curve and the area under curve (AUC) when variables or biomarkers are subject to measurement error. We propose a valid procedure to handle measurement error effects and estimate the parameters in the cure model, as well as the AUC. We also make an effort to establish the theoretical properties with rigorous justification.
dc.format.extent 100 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Mathematics, Vol.13, No.3, 424
dc.subject (關鍵詞) area under curve; bias correction; cure; censoring; EM algorithm; incomplete response; insertion method; mismeasurement
dc.title (題名) Analysis of receiver operating characteristic curves for cure survival data and mismeasured biomarkers
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.3390/math13030424
dc.doi.uri (DOI) https://doi.org/10.3390/math13030424