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    题名: Analysis of length-biased and partly interval-censored survival data with mismeasured covariates
    作者: 陳立榜
    Chen, Li-Pang;Qiu, Bangxu
    贡献者: 統計系
    关键词: AFT model;biased sampling;boosting;Buckley–James formulation;incomplete data;mea-surement error correction;SIMEX;variable selection
    日期: 2023-12
    上传时间: 2023-11-30 14:58:43 (UTC+8)
    摘要: 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.
    關聯: Biometrics, Vol.79, No.4, pp.3929-3940
    数据类型: article
    DOI 連結: https://doi.org/10.1111/biom.13898
    DOI: 10.1111/biom.13898
    显示于类别:[統計學系] 期刊論文

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