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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/148386


    Title: Analysis of length-biased and partly interval-censored survival data with mismeasured covariates
    Authors: 陳立榜
    Chen, Li-Pang;Qiu, Bangxu
    Contributors: 統計系
    Keywords: AFT model;biased sampling;boosting;Buckley–James formulation;incomplete data;mea-surement error correction;SIMEX;variable selection
    Date: 2023-12
    Issue Date: 2023-11-30 14:58:43 (UTC+8)
    Abstract: In this paper, we analyze the length-biased and partly interval-censored data, whose challenges primarily come from biased sampling and interfere induced by interval censoring. Unlike existing methods that focus on low-dimensional data and assume the covariates to be precisely measured, sometimes researchers may encounter high-dimensional data subject to measurement error, which are ubiquitous in applications and make estimation unreliable. To address those challenges, we explore a valid inference method for handling high-dimensional length-biased and interval-censored survival data with measurement error in covariates under the accelerated failure time model. We primarily employ the SIMEX method to correct for measurement error effects and propose the boosting procedure to do variable selection and estimation. The proposed method is able to handle the case that the dimension of covariates is larger than the sample size and enjoys appealing features that the distributions of the covariates are left unspecified.
    Relation: Biometrics, Vol.79, No.4, pp.3929-3940
    Data Type: article
    DOI link: https://doi.org/10.1111/biom.13898
    DOI: 10.1111/biom.13898
    Appears in Collections:[Department of Statistics] Periodical Articles

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