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題 名 | 右方設限長期存活資料比率之研究=The Proportion of Long-Term Survivor Data in Right Censored Case |
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作 者 | 蘇秀媛; 蘇志雄; 謝鑫能; | 書刊名 | 作物、環境與生物資訊 |
卷 期 | 2:2 民94.06 |
頁 次 | 頁95-104 |
分類號 | 434.28 |
關鍵詞 | 治癒資料; 長期存活資料; 右方設限; 蒙地卡羅統計模擬; 最大概度法; Cured data; Long-term survivor data; Right-censored; Monte Carlo simulation; Maximum likelihood ratio test; |
語 文 | 中文(Chinese) |
中文摘要 | 摘要 自從Boag (1949)提出「治癒資料」的 分析方法後,部分學者將此方法成功的應用 在醫學資料的分析。本篇文章稱Boag 所提 的「治癒資料」為「長期存活資料」,亦即 在存活資料中,若實驗期間能無限延長下, 有部份資料都能永久存活。對於此類資料, 我們延用Boag 的方法,定義在右方設限資 料下概度函數,並假設存活母體為指數分布 與Weibull 分布,導出「長期存活資料」比 率之最大概度估計式及概度比檢定,同時利 用Kaplan and Meier 的估計方法,提出無 母數方法來估計「長期存活資料」比率及檢 定方法。本文利用蒙地卡羅統計模擬方法比 較在最大概度法及無母數方法不同情形 下,觀察「長期存活資料」比率的狀況,發 現在中、低設限下,無母數方法在檢定「長 期存活資料」比率的檢定力優於最大概度 法。 |
英文摘要 | ABSTRACT Since the method for analyzing the cured data was proposed by Boag in 1949, it has been applied to many medical data successfully by other scholars. The “cured data” in Boag’s paper was renamed as “long-term survival data” here. The long-term survival data means some of the data can survive in indefinite time. The likelihood function with right-censored data was defined by using Boag’s method. The survival population was assumed to be exponential distribution or Weibull distribution. The MLE (maximum likelihood estimator) and LRT (likelihood ratio test) can be derived for long-term survival data. Furthermore, a nonparametric method for estimating proportion of long-term survival data was derived based on Kaplan-Meier’s estimation. In this paper, we compare the MLE and non-parametric method by Monte Carlo simulation method for long-term survival data. We find that the performance of non-parametric test is better than that of maximum likelihood ratio test in cases of middle censored rate and low censored rate. |
本系統中英文摘要資訊取自各篇刊載內容。