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| Title: | 基於應變數測量誤差之下的函數型加速失效模型估計法
Estimation of Accelerated Functional Failure Time Models with Error-Prone Response |
| Authors: | 黃筱庭
Huang, Hsiao-Ting |
| Contributors: | 陳立榜
Chen, Li-Pang
黃筱庭
Huang, Hsiao-Ting |
| Keywords: | 加速失效模型
提升法
測量誤差
校正迴歸
存活分析
變數選擇
accelerated failure time model
boosting
measurement error
regression calibration
survival analysis
variable selection |
| Date: | 2023 |
| Issue Date: | 2023-08-02 13:03:09 (UTC+8) |
| Abstract: | 在存活分析中，常透過參數型加速失效模型描述自變數與存活時間之間的關係。在基於此模型架構並假設資料能被精準測量下，許多估計方法被提出以估計其參數。然而，自變數與存活時間之間的關係可能為非線性，且資料帶有測量誤差。在本論文中，我們考慮了資料帶有分類錯誤及測量誤差之函數型加速失效模型，並透過插入校正(insertion correction strategy)與迴歸校正(regression calibration)處理測量誤差，再利用提升法(boosting)估計自變數與活存時間之間的線型及非線性關係。從數值分析結果可知，提出之方法能提升估計表現並辨別重要變數，此方法並進一步應用在荷蘭癌症研究所提供之乳癌資料上以分析病人存活時間與基因表現之關係。
In survival analysis, accelerated failure time (AFT) models in the parametric form are commonly used to describe the relationship between survival time and covariates. Many methods have been proposed to estimate the parameter under this model with data assumed to be precisely measured. In applications, however, covariates are possibly non-linear with the survival time, which is possibly contaminated by measurement error. In this thesis, we consider the accelerated functional failure time model with survival data subject to measurement error. We use insertion correction strategy and regression calibration to correct for misclassification and error-prone survival time, respectively. Based on the corrected data, we use the boosting algorithm with the cubic spline estimation method to iteratively recover non-linear relationship between covariates and survival time. Theoretically, we justify the validity of measurement error correction and estimation procedure. Numerical studies show that the proposed method improves the performance of estimation and is able to capture informative covariates. The methodology is implemented to the breast cancer data provided by the Netherlands Cancer Institute for research. |
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| Description: | 碩士
國立政治大學
統計學系
110354005 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110354005 |
| Data Type: | thesis |
| Appears in Collections: | [統計學系] 學位論文
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