時間相依AUC與預測精準度-以半母數風險迴歸模型為例

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孫薇婷(Wei-Ting Sun) 查詢紙本館藏

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論文名稱

時間相依AUC與預測精準度-以半母數風險迴歸模型為例

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摘要(中)

在現今的醫學研究中，每當病人進入實驗都會記錄其共變數數值，
例如: 存活時間、血壓、血型等，我們可將與時間相依的共變數作為
生物指標以衡量疾病的預測能力。在傳統醫學研究上，通常會使用接
受者作業特徵曲線(Receiver Operating Characteristic Curve，或者叫ROC 曲線) 作為衡量疾病預測能力的標準。先前的研究中亦發展了固定共變數下時間相依敏感度與特異度之 Cox 風險迴歸模型。然而
當比例風險假設不符合時，即不適用一般的 Cox 風險迴歸模型，在此
我們建議可使用加速失效模型(Accelerated Failure Time Model)作為替代。接著，我們進一步將其推廣到長期追蹤共變數的資料。並於模擬與實例分析中，比較傳統模型衡量指標?? square與一致性指標??，以評估兩者模型預測能力之表現。

摘要(英)

In current medical research, whenever a patient enters an experiment, they will record their covariate values, such as: survival time, blood pressure, blood type, etc.
We can use these time-dependent covariates as biomarkers to measure and predict disease. In traditional medical research, the Receiver Operating Characteristic Curve (or called ROC curve) is often used as a measure of disease
prediction ability. Previous studies have also developed Cox regression models with time-dependent sensitivity and specificity for fixed covariates. However, when the proportional assumption is not fit, the general Cox regression model is not applicable. Here, we suggest that an Accelerated Failure Time Model can be used as an alternative. Then, we further extended it to the longitudinal covariate data. In the simulation and example analysis, the traditional model index ?? square
and the consistency index C were compared to evaluate the performance of the prediction ability of the two models.

關鍵字(中)

★ 接受者作業特徵曲線下面積
★ 時間相依接受者作業特徵曲線下面積
★ 一致性指標
★ 預測
★ Cox 風險迴歸模型
★ 加速失效模型
★ 事件型敏感度
★ 動態型特異度
★ R square

關鍵字(英)

論文目次

目錄
第一章緒論 1
1.1 ROC 曲線之架構…………………………………………………………...2
1.1.1 傳統敏感度與特異度…………………………………………………2
1.1.2 ROC 圖型……………………………………………………………..3
1.1.3 計算方法……………………………………………………………....3
1.2 接受者作業特徵曲線下面積(Area Under The ROC Curve；簡稱 AUC)...8
1.3 ROC 曲線的推廣……………………………………………………….....11
第二章統計方法 14
2.1 聯合模型 (Joint Model) …………………………………………………..14
2.2 存活模型…………………………………………………………………...17
2.2.1 Cox 比例風險模型……………………………………………………..17
2.2.2 加速失效模型 (AFT Model) ………………………………………......20
2.3 模型衡量指標…………………………………………………………..….23
2.3.1 一致性指標 Concordance…………………………………………….....23
2.3.2 模型衡量指標 ??
2……………………………………………………...25
第三章模擬研究 27
3.1 固定共變數…………………………………………………………..…….27
3.1.1 Weibull-Cox 模型下之模擬研究…………………………………...…..27
3.1.2 Weibull-AFT模型下之模擬研究……………………………………….31
3.1.3 Loglogistic-Cox 模型下之模擬研究…………………………………....35
3.1.4 Loglogistic-AFT 模型下之模擬研究………………………………...…39
3.1.5 Lognormal-Cox 模型下之模擬研究…………………………………....44
3.1.6 Lognormal-AFT 模型下之模擬研究…………………………………...48
3.2 模型衡量指標之模擬研究………………………………………………...53
第四章資料分析 56
4.1 資料背景介紹與分析……………………………………………………...56
4.2 分析結果…………………………………………………………………...57
第五章結論 65
參考文獻 67
圖目錄
圖 1…………………………………………………………………………………...6
圖 2…………………………………………………………………………………..10
圖 3…………………………………………………………………………………..30
圖 4…………………………………………………………………………………..34
圖 5…………………………………………………………………………………..38
圖 6…………………………………………………………………………………..43
圖 7………………………………………………………………………………..…47
圖 8…………………………………………………………………………………..52
圖 9……………………………………………………………………………….….59
圖 10………………………………………………………………………………....59
圖 11………………………………………………………………………………....60
圖 12………………………………………………………………………………....61
圖 13………………………………………………………………………………....61
圖 14………………………………………………………………………………....63
圖 15………………………………………………………………………………....63
表目錄
表 1………………………………………………………………………………….....5
表 2…………………………………………………………………………………….5
表 3………………………………………………………………………………...…..9
表 4……………………………………………………………………………….…..29
表 5…………………………………………………………………………….……..33
表 6…………………………………………………………………………………...37
表 7…………………………………………………………………………………...42
表 8………………………………………………………………………………..….46
表 9……………………………………………………………………………...……51
表 10………………………………………………………………………………….53
表 11……………………………………………………………………………….…54
表 12………………………………………………………………………………….55
表 13……………………………………………………………………………….....55
表 14……………………………………………………………………………….…58
表 15……………………………………………………………………………….…62

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指導教授

曾議寬

審核日期

2018-7-25

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