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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/76943

    Title: 具共變量誤差之區間設限數據分析
    Other Titles: Analysis of Interval-Censored Data with Mismeasured Covariates
    Authors: 溫啟仲
    Contributors: 淡江大學數學學系
    Keywords: 有效分數;現狀數據;區間設限;測量誤差;Conditional score;current status data;interval censoring;measurement error
    Date: 2011-08
    Issue Date: 2012-05-22 22:16:47 (UTC+8)
    Abstract: 具共變量測量誤差之右設限數資料已被廣泛的研究,但對現狀或區間設限數據卻很 少研究。研究動機的一部分為斑馬魚之基底細胞癌的研究,其中研究者只知道細胞癌的 發生時間在獻祭時間之前或之後,而共變量Sonic hdgehog 基因表現存有量測誤差。因 此,我們對於具共變量測量誤差之(型I 或型k)區間設限資料,在正比例優劣比模型下, 將提出一個「條件分數法」來分析。條件分數法的重要優勢為不需對真實易有誤差卻未 見之共變量作一分佈假設,因此我們所提估計方法將相較其他處理測量誤差方法更具穩 健性。
    Covariate measurement error problems have been extensively studied in the context of right-censored data but less so for current status or interval-censored data. Motivated partly by the zebrafish basal cell carcinoma (BCC) study, where the occurrence time of BCC was only known to lie before or after a sacrifice time and where the covariate (Sonic hedgehog expression) was measured with error, we will propose a conditional score approach to the analysis of (case I / case k) interval-censored data with mismeasured covariates under the proportional odds model. The conditional score approach, originated by Stefanski and Carroll (1987), has the important advantage that it does not need a distributional assumption for unobserved error-prone covariate, rendering the proposed approach more robust and applicable compared to other strategies for handling measurement errors.
    Appears in Collections:[數學學系暨研究所] 研究報告

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