A Nonparametric Regression Calibration for the Accelerated Failure Time Model With Measurement Error
學年 113
學期 1
出版（發表）日期 2024-12-30
作品名稱 A Nonparametric Regression Calibration for the Accelerated Failure Time Model With Measurement Error
作品名稱（其他語言）
著者 Huang, Yih-huei; Wu, Chien-ying
單位
出版者
著錄名稱、卷期、頁數 Statistics in Medicine 43(30),　p.6073-6085
摘要 Accelerated failure time models are appealing due to their intuitive interpretation. However, when covariates are subject to measurement errors, naive estimation becomes severely biased. To address this issue, the regression calibration (RC) approach is a widely applicable and effective method. Traditionally, the RC method requires a good predictor for the true covariate, which can be obtained through parametric distribution assumptions or validation datasets. Consequently, the performance of the estimator depends on the plausibility of these assumptions. In this work, we propose a novel method that utilizes error augmentation to duplicate covariates, facilitating nonparametric estimation. Our approach does not require a validation set or parametric distribution assumptions for the true covariate. Through simulation studies, we demonstrate that our approach is more robust and less impacted by heavy censoring rates compared to conventional analyses. Additionally, an analysis of a subset of a real dataset suggests that the conventional RC method may have a tendency to overcorrect the attenuation effect of measurement error.
關鍵字 accelerated failure time;error augmentation;measurement errornonparametric regression;regression calibration;
語言 en
ISSN 1097-0258
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 TWN
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/127323 )