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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 張淑惠(Shu-Hui Chang) | |
dc.contributor.author | Zih-Hao Chen | en |
dc.contributor.author | 陳子豪 | zh_TW |
dc.date.accessioned | 2021-06-13T15:20:21Z | - |
dc.date.available | 2008-08-14 | |
dc.date.copyright | 2008-08-14 | |
dc.date.issued | 2008 | |
dc.date.submitted | 2008-07-23 | |
dc.identifier.citation | Andersen, P. K., Borgan, Ø., Gill, R. D. and Keiding, N. (1993), “Statistical Models Based on Counting Processes.” Springer-Verlag, New York.
Chang, S. H. and Tzeng, S. J. (2006). “Nonparametric estimation of sojourn time distribution for truncated serial event data – a weight-adjusted approach.” Lifetime Data Anal, 12, 53-67. Cox, D. R. (1972). “Regression Models and Life Tables.” Journal of the Royal Statistical Society, Series B, 34, 187-220. Crowder, M. (2001). “Classical Competing Risks.” Chapman & Hall/CRC. Fine, J.P. and Gray, R.J. (1999). “A Proportional Hazards Model for the Subdistribution of a Competing Risk.” Journal of the American Statistical Association, 94,446,496-509 Huang, Y. and Wang, M. C. (1995). “Estimating the Occurrence Rate for Prevalent Survival Data in Competing Risks Models.” Journal of the American Statistical Association, 90,1406-1415. Kalbfleish, J. D. and Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data. John Wiley & Sons,Ltd . Liou, H.H. , Wu, C.Y., Chiu, Y.H., Yen, A.M.F., Chen, R.C., Chen, T.F., Chen, C.C., Hwang, Y.C., Wen, Y.R., Chen, T.H.H. (2008). “Natural History and Effectiveness of Early Detection of Parkinson’s Disease : Results from Two Community-Based Programmes in Taiwan (KCIS no. 11).” Journal of Evaluation in Clinical Practice, 14, 198-202. Peng, L. and Fine, J.P. (2006). “Nonparametric estimations with left-truncated semicompeting risks data.” Biometrika, 93,367-383 Pintilie, M. (2006). “Competing Risks – A Practical Perspective .” John Wiley & Sons,Ltd Prentice, R. L., and Kalbfleish, J. D. and Peterson, A. V. and Flournoy, N. and Farewell, V. T. and Breslow, N. E. (1978). “The Analysis of Failure Times in the Presence of Competing Risks.” Biometrics, 34, 541-554. Tsiatis, A. A. (1975). “A Nonidentifiability Aspect of the Problem of Competing Risks.” Proc. Nat. Acad. Sci. 72, 20-2. Wang, M. C., (1991). “Nonparametric Estimation from Cross-Sectional Survival Data.” Journal of the American Statistical Association, 86, 130-142. Wang, M. C., (1996). “Hazards Regression Analysis with Length-Biased Data.” Biometrika, 83, 343-354. Wang, M. C. and Brookmeyer, R. and Jewell, N. P. (1993). “Statistical Models For Prevalent Cohort Data.” Biometrics, 49, 1-11. 曾信嘉 (2002) 截切連續事件資料之統計分析。 國立台灣大學公共衛生學院流行病學研究所生物醫學統計組博士論文。 鄭榕鈺 (2003) 競爭路徑資料之統計分析。 國立台灣大學公共衛生學院流行病學研究所生物醫學統計組博士論文。 戴政, 江淑瓊 (2000) 生物醫學統計概論。台北:翰蘆圖書出版有限公司。 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37161 | - |
dc.description.abstract | 隨著醫學的進步,長期追蹤研究中描述疾病演化狀態的多狀態資料便廣泛的被討論。部分競爭風險資料便是一種終止事件會使中繼事件設限之多狀態資料。將截切部分競爭風險資料加上人工截切後,以競爭風險資料型態進行討論是較為簡易的分析方法。由於左截切部分競爭風險資料不同於左截切競爭風險資料之收集方式,若將左截切部分競爭風險資料以競爭風險資料型態進行分析,則會因人工截切而捨棄部分觀測資料中的資料訊息,此時若人工截切刪去過多觀測資料的中繼事件訊息,則容易造成參數估計的不穩定。因此本文利用對比風險模式,在假設獨立截切與設限的條件下,分別考慮中繼事件時間與終止事件時間獨立與相依的情況,討論不使用人工截切之對比風險模式的迴歸參數估計方式。藉由模擬評估所提之估計方式與傳統左截切競爭風險資料型態的迴歸參數估計方法在不同觀測比例上的表現。本文亦將所提之參數估計方法應用至大腸直腸癌的實際資料上。 | zh_TW |
dc.description.abstract | In the development of the medical science, the multi-state data consisting of the course of disease progression are frequently encountered in longitudinal studies. The semicompeting risks data is a type of multi-state data where an intermediate event may be censored by a terminal event. When the terminal event is subject to left truncation, the naive regression analysis for the intermediate event based on the competing risks data in the presence of left truncation, only use part of data and the information of the observed intermediate event may be excluded by artificial truncation which may lead to large efficiency loss. For estimating the regression parameters in the relative risks model of the cause-specific hazard function for the intermediate event, estimation methods using all intermediate event information are developed under the situations of the independent and dependent terminal events respectively. Simulation studies are conducted to compare the performance of the proposed and naive estimators. Finally, we also apply those methods to analyze a colon cancer data set. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T15:20:21Z (GMT). No. of bitstreams: 1 ntu-97-R95842025-1.pdf: 442111 bytes, checksum: 63d7a5782d04ab83aed7a4ef1b3cdf17 (MD5) Previous issue date: 2008 | en |
dc.description.tableofcontents | 第一章 導論......1
第一節 前言......1 第二節 左截切部分競爭風險資料......2 第三節 研究動機......4 第二章 文獻回顧......6 第一節 左截切部分競爭風險資料之無母數估計方法......6 第二節 競爭風險資料之子分佈風險函數估計方法......8 第三節 利用權數校正截切序列資料之無母數估計方法......10 第三章 方法......13 第一節 競爭風險模式......15 第二節 在中繼事件時間與終止事件時間獨立下之迴歸參數估計 ......19 第三節 在中繼事件時間與終止事件時間相依下之迴歸參數估計 ......21 第四章 統計模擬與實例分析......24 第一節 模擬資料生成......24 第二節 模擬結果......27 第三節 實際資料......28 第五章 結果與討論......30 附錄一 模擬情境一......32 附錄二 模擬情境二......44 參考文獻......59 | |
dc.language.iso | zh-TW | |
dc.title | 探討左截切半競爭風險資料之對比風險模型的迴歸參數估計 | zh_TW |
dc.title | A Proportional Hazards Model for Left-truncated Semicompeting Risks Data | en |
dc.type | Thesis | |
dc.date.schoolyear | 96-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 戴政,陳秀熙,曾信嘉 | |
dc.subject.keyword | 競爭風險資料,部分競爭風險資料,對比風險模式,人工截切, | zh_TW |
dc.subject.keyword | Artificial truncation,Competing risks data,Proportional hazards model,Semicompeting risks data, | en |
dc.relation.page | 60 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2008-07-24 | |
dc.contributor.author-college | 公共衛生學院 | zh_TW |
dc.contributor.author-dept | 流行病學研究所 | zh_TW |
顯示於系所單位: | 流行病學與預防醫學研究所 |
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