右方設限資料下兩個存活函數比率聯合信賴界限之研究

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蔡立杰(Li-chieh Tsai) 查詢紙本館藏

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統計研究所

論文名稱

右方設限資料下兩個存活函數比率聯合信賴界限之研究
(A study of simultaneous confidence bounds for rato of two survival functions with right censored data)

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摘要(中)

某一種新藥想成為專利藥的合格替代藥品必須通過非劣性檢定。目
前文獻中針對右方設限存活資料，是根據建構信賴界限進行非劣性檢定。本文根據Freitag 等人(2006)提出的逐點檢定及最小上界檢定、Parzen 等人(1997)提出一個模擬方法及McKeaague 和Zhao(2002)以經驗概似函數建構之四個不同的信賴下界及在資料符合比例風險假設下，用Cox 模型推導出信賴下界。本文藉由模擬研究探討所提的五種信賴下界的覆蓋機率及與真實質之差距。最後，以一個實例說明上述五種信賴下界之應用。

摘要(英)

A new drug to become a alternative medicine of a qualified patent medicine must be through non-inferiority test. Currently literature for right censored survival data is based on constructing a confidence bound for non-inferiority test. In this article, we proposed four different confidence bounds based on Freitag et al (2006) proposed pointwise test, and supremum test, Parzen et al (1997) proposed a simulation method, McKeaague and Zhao (2002) has constructed empirical likelihood function. And the data meet the proportional hazards assumption, using
Cox models derived a confidence bound. A simulation study is then conducted to compare the coverage probability and the difference between the proposed confidence bounds and the true value. Finally, the application of the proposed confidence bounds is illustrated by using a real data.

關鍵字(中)

★ 非劣性檢定
★ 聯合信賴界限

關鍵字(英)

★ non-inferiority test
★ simultaneous confidence bounds

論文目次

摘要.................................................... i
Abstract ............................................... ii
誌謝辭............................................... iii
目錄.................................................... v
表目錄............................................... vii
圖目錄.............................................. viii
第一章研究之動機與目的.................................. 1
第二章文章回顧.......................................... 5
2.1 逐點檢定......................................... 5
2.2 最小上界檢定..................................... 7
2.3 模擬方法......................................... 9
2.4 經驗概似函數法................................... 11
第三章統計方法......................................... 18
3.1 在Cox模型下之非劣性檢定.......................... 18
3.2 在無母數假設下之非劣性檢定....................... 22
第四章模擬研究......................................... 26
4.1 模擬方法......................................... 26
4.2 模擬結果......................................... 27
vi
第五章實例分析......................................... 30
第六章結論與討論....................................... 33
參考文獻................................................ 35

參考文獻

1. Andersen, P. K., Borgan, O., Gill, R. D., and Keiding, N. (1993). Statistical Models Based on Counting Processes. Series in Statistics. Spinger: New York.
2. Berger, R. L. (1982). Multiparameter hypothesis testing and acceptance sampling. Technometrics 24, 295-300.
3. Billingsley, P. (1968). Convergence of Probability Measures. Series in Probability and Mathematical Statistics. New York: Wiley.
4. Bristol, D.R. (1993). Planning survival studies to compare a treatment to an active control. Journal of Biopharmaceutical Statistics 3, 153-158.
5. Com-Nougue, C., Rodary, C., and Patte, C. (1993). How to establish equivalence when data are censored: A randomized trial of treatment for B non-Hodgkin lymphoma. Statistics in Medicine 12, 1353-1364.
6. Fleming, T. R. (1990). Evaluation of active control trials in AIDS. Journal of Acquired Immune Deficiency Syndromes 3, S82-S87.
7. Fleming, T. R. and Harrington, D. P. (1991). Counting processes and survival analysis. Series in Probability and Mathematical Statistics. New York: Wiley.
8. Freitag, G. and Munk, A. (2005). Consistency of bootstrap procedures for the nonparametric assessment of non inferiority with random censorship. Technical Report, Georg-Augaust-Universität Göttingen, Germany.
9. Freitag, G., Lange, S., and Munk, A. (2006). Nonparametric assessment of noninferiority with censored data. Statistics in Medicine 25, 1201-1217.
10. Kalbfleisch, J. D. and Prentice, R. L. (1980). The Statistical Analysis of Failure Time Data. New York: Wiley.
11. McKeague, I. W. and Zhao, Y. (2002). Simultaneous confidence bands for ratios of survival functions via empirical likelihood. Statistics & Probability Letters 60, 405-415.
12. Parzen, M. I., Wei, L. J., and Ying, Z. (1997). Simultaneous confidence intervals for the difference of two survival functions. Scandinavian Journal of Statistics 24, 309-314.
13. Rothmann, M., Li, N., Chen, G., Chi, G. Y. H., Temple, R., and Tsou, H. H. (2003). Design and analysis of non-inferiority mortality trials in oncology. Statistics in Medicine 22, 239-264.
14. Shao, J. and Tu, D. (1995). The Jackknife and Bootstrap. Series in Statistics. Spinger: New York.
15. Stallard, N. and Whitehead, A. (1996). An alternative approach to the analysis of animal carcinogenicity studies. Regulatory Toxicology and Pharmacology 23, 244-248.
16. Su, J. Q. and Wei, L. J. (1993). Nonparametric estimation for the difference or ratio of median failure times. Biometrics 49, 603-607.
17. Wei, L. J. and Gail, M. H. (1983). Nonparametric estimation for a scale-change with censored observations. Journal of the American Statistical Association 78, 382-388.
18. Wellek, S. (1993). A log-rank test for equivalence of two survivor functions. Biometrics 49, 877-881.
19. Wiens, B. (2002). Choosing an equivalence limit for non-inferiority or equivalence studies. Controlled Clinical Trials 23, 2-14.

指導教授

陳玉英(Yuh-ing Chen)

審核日期

2010-7-14

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