政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/142017

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政大機構典藏 > 商學院 > 統計學系 > 期刊論文 > Item 140.119/142017

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/142017

Title:	Analysis of noisy survival data with graphical proportional hazards measurement error models
Authors:	陳立榜 Chen, Li-Pang Yi, Grace Y.
Contributors:	統計系
Keywords:	error-prone variable;graphical model;high-dimensionality;simulation-extrapolation;survivalanalysis
Date:	2021-09
Issue Date:	2022-09-21 11:45:24 (UTC+8)
Abstract:	In survival data analysis, the Cox proportional hazards (PH) model is perhaps the most widely used model to feature the dependence of survival times on covariates. While many inference methods have been developed under such a model or its variants, those models are not adequate for handling data with complex structured covariates. High-dimensional survival data often entail several features: (1) many covariates are inactive in explaining the survival information, (2) active covariates are associated in a network structure, and (3) some covariates are error-contaminated. To hand such kinds of survival data, we propose graphical PH measurement error models and develop inferential procedures for the parameters of interest. Our proposed models significantly enlarge the scope of the usual Cox PH model and have great flexibility in characterizing survival data. Theoretical results are established to justify the proposed methods. Numerical studies are conducted to assess the performance of the proposed methods.
Relation:	Biometrics, Vol.77, No.3, pp.956-969
Data Type:	article
DOI 連結:	https://doi.org/10.1111/biom.13331
DOI:	10.1111/biom.13331
Appears in Collections:	[統計學系] 期刊論文

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