博碩士論文 942205001 詳細資訊




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姓名 陳安朋(An-peng Chen)  查詢紙本館藏   畢業系所 統計研究所
論文名稱 有序雙重事件時間分析使用與時間相關的共變數-邊際方法的比較
(Ordered Bivariate Survival Time with Time Dependent Covariate -Comparison of Marginal Method)
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摘要(中) 台灣地區的衛生署自1997年4月開始免費提供「雞尾酒療法」之治療藥物給全國各愛滋病指定醫院的病患使用,至今已達十年之久。我們感興趣的是雞尾酒療法對於愛滋病發病前後的療效差異,故本篇使用台灣地區136個愛滋病患的資料,焦點放在多維存活時間的邊際方法,如AG(Andersen and Gill, 1982)模型、WLW(Wei, Lin, and Wiessfeld, 1989)模型和PWP(Prentice, Williams and Petersen, 1981)模型之比較,並探討使用雞尾酒療法,對於兩段存活時間,愛滋病毒檢驗呈現陽性到發病的時間和愛滋病發病到死亡的時間,療效之差異及CD4細胞數量之影響。
摘要(英) The Department of Health in Taiwan began to freely provide the treatment of HAART (highly active antiretroviral therapy) for the AIDS patients in the appointed hospitals all over the country ever since April, 1997 and up to now, reach a decade period. We are interested in the different effects of HAART to the 136 AIDS patients before and after the onset of AIDS. To investigate this research problem, we focus on three marginal approaches, the AG (Andersen and Gill, 1982) model, WLW (Wei, Lin, and Wiessfeld, 1989) model and PWP (Prentice, Williams and Petersen, 1981) model. In addition to compare the performance of the three approaches, we also study the effect of CD4 count to both survival times.
論文目次 中文摘要...................................................i
英文摘要..................................................ii
誌謝辭...................................................iii
目錄.....................................................iii
圖目錄.....................................................v
表目錄....................................................vi
第一章 緒論................................................1
第二章 統計方法............................................5
2.1 三種邊際方法介紹....................................5
2.1.1 WLW模型.......................................5
2.1.2 AG模型和PWP模型...............................8
2.2 模型配適............................................9
第三章 模擬研究...........................................12
第四章 實例分析...........................................15
第五章 結論...............................................18
參考文獻..................................................19
附錄......................................................22
參考文獻 1. Andersen, P. K. and Gill, R. D.(1982). Cox's regression model for counting processes: A large sample study. Annals of Statistics, 10:1100-1120.
2. Cai, J. and Prentice, R. L.(1995). Estimating equations for hazard ratio parameters based on correlated failure time data. Biometrika, 82:151–164.
3. Clayton, D. G.(1978). A model for association in bivariate life tables and its application in epidemiological studies of chronic disease incidence. Biometrika, 65:141–151.
4. Clayton, D. G. and Cuzick, J.(1985). Multivariate generalisations of the proportional hazards model. Journal of the Royal Statistical Society, Series A, 148:82–117.
5. Clegg, L. X., Cai, J. and Sen, P. K.(1999). A marginal mixed baseline hazards model for multivariate failure time data. Biometrics, 55: 805–812.
6. Cox, D. R.(1972). Regression models and life-tables (with Discussion). Journal of the Royal Statistical Society:Series B, 34:187-220.
7. Cox, D. R.(1975). Partial likelihood. Biometrika, 62:269-276.
8. Cook, R. J. and Lawless, J. F.(2002). Analysis of repeated events. Statistical Methods for Medical Research, 11:141–166.
9. Finkelstein, D. M., Schoenfeld, D. A. and Stamenovic, E.(1997). Analysis of multiple failure time data from an AIDS clinical trial. Statistics in Medicine, 16:951-961.
10. Huber, P. J.(1967). The behaviour of maximum likelihood estimates under non-standard conditions. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, 1:221–233.
11. Huster, J. H., Brookmeyer, R. and Self, S. G.(1989). Modelling paired survival data with covariates. Biometrics, 45:145-156.
12. Lawrance, A. J. and Lewis, P. A. W.(1981). A New Autoregressive Time Series Model in Exponential Variables (NEAR(1)). Advances in Applied Probability, 13:826-845.
13. Lee, E. W.,Wei, L. J. and Amato, D. A.(1992). Cox-type regression analysis for large numbers of small groups of correlated failure time observations. In Klein, J. P. and Goel, P. K. (eds), Survival Analysis: State of the Art. Kluwer: Dordrecht, pp. 237–247.
14. Lin, D. Y. and Wei, L. J.(1989). The robust inference for the Cox proportional hazard model. Journal of the American Statistical Association, 84:1074-1078.
15. Lin, D. Y.(1993). MULCOX2: a general computer program for the Cox regression analysis of multivariate failure time data. Computer Methods and Programs in Biomedicine, 40:279-293.
16. Lin, D. Y.(1994). Cox regression analysis of multivariate failure time data: the marginal approach. Statistics in Medicine, 13:2233-2247.
17. Lin, D. Y., Wei, L. J., Yang, I. and Ying, Z.(2000). Semiparametric regression for the mean and rate functions of recurrent events. Journal of the Royal Statistical Society, Series B, 62:711–730.
18. Oakes, D.(1982). A model for association in bivariate survival data. Journal of the Royal Statistical Society, Series B, 44:414–422.
19. Pepe, M. S. and Cai, J.(1993). Some graphical displays and marginal regression analyses for recurrent failure times and time-dependent covariates. Journal of American Statistical Association, 88: 811–820.
20. Prentice, P. L., Williams, B. J. and Peterson, A. V.(1981). On the regression analysis of multivariate failure time data. Biometrika, 68:373-379.
21. Rubin, D. B.(1976). Inference and missing values. Biometrika, 63:81-92.
22. Schaubel, D. E. and Cai, J. (2005). Analysis of clustered recurrent event data with application to hospitalization rates among renal failure patients. Biostatistics, 6:404–419.
23. Spiekerman, C. F. and Lin, D. Y.(1998). Marginal regression models for multivariate failure time data. Journal of American Statistical Association, 93: 1164–1175.
24. Therneau, T. M. and Grambsch, P. M. (eds)(2000). Modeling survival data:extending the Cox Model. Springer: New York.
25. Vaupel, J. W., Manton, K. G. and Stallard, E.(1979). The impact of heterogeneity in individual frailty on the dynamics of mortality. Demography, 16:439–454.
26. Wei, L. J., Lin, D. Y., and Weissfeld, L.(1989). Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. Journal of American Statistical Association, 84:1065-1073.
指導教授 曾議寬(Yi-kuan Tseng) 審核日期 2007-6-24
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