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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張淑惠(Shu-Hui Chang) | |
| dc.contributor.author | Tung-Yang Chou | en |
| dc.contributor.author | 周東陽 | zh_TW |
| dc.date.accessioned | 2021-06-08T04:30:56Z | - |
| dc.date.copyright | 2010-03-12 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-11-27 | |
| dc.identifier.citation | Beaudoin, D. and Chaieb, L.L. (2008). Archimedean copula model selection under
dependent truncation. Statistics in medicine, 27, 4440-4454. Betensky, R.A. and Martin, E.C. (2003). Commentary: Failure-rate functions for doubly-truncated random variables. IEEE Transactions on reliability, 52, 7-8. Bhattacharya, P.K., Chernoff, H. and Yang, S.S. (1983). Nonparametric estimation of the slope of a truncated regression. The Annals of Statistics, 11, 505-514. Bilker, W.B. and Wang, M.C. (1996). A semiparametric extension of the Mann-Whitney test for randomly truncated data. Biometrics, 52, 10-20. Chang, S.H. and Yeh, S.W. (2003). Semiparametric estimation of survival function for doubly truncated data. Journal of the Chinese Statistical Association, 41, 443-460. Chen, Y.Q. and Jewell, N.P. (2001). On a general class of semiparametric hazards regression models. Biometrika, 88, 687-702. Chi, Y.C., Tsai W.Y. and Hu, C.L. (2004). Testing the equality of two survival functions with doubly truncated data. Journal of the Chinese Statistical Association, 42, 223-244. Efron, B. and Petronsian, V. (1999). Nonparametric methods for doubly truncated data. Journal of the American Statistical Association, 94, 824-834. Fygenson, M. and Ritov, Y. (1994). Monotone estimating functions for censored data. The Annals of Statistics, 22, 732-746. Gehan, E.A. (1965). A generalized Wilcoxon test for comparing arbitrarily single-censored samples. Biometrika, 52, 203-223. Gross, S.T. and Lai, T.L. (1996). Nonparametric estimation and regression analysis with left-truncated and right-censored data. Journal of the American Statistical Association, 91, 1166-1180. Kalbfleisch, J.D. and Prentice, R.L. (2002). The Statistical Analysis of Failure Time Data, 2nd Edition. John Wiley and Sons, Inc., New York. Khan, S. and Lewbel, A. (2007). Weighted and two-stage least squares estimation of semiparametric truncated regression models. Economic Theory, 23, 309-347. Lai, T.L. and Ying, Z. (1991). Rank regression methods for left-truncated and right-censored data. The annals of Statistics, 19, 531-556. Lai, T.L. and Ying, Z. (1992). Linear rank statistics in regression analysis with censored or truncated data. Journal of Multivariate Analysis, 40, 13-45. Lee, A.J. (1990). U-statistics. New York: Marcel Dekker. Lynden-Bell, D.(1971).A method of allowing for known observational selection in small samples applied to 3CR quasars. Monograph National Royal Astronomical Society, 155, 95-118. Martin, E.C. and Betensky, R.A. (2005). Testing quasi-independence of failure and truncation via conditional Kendall’s tau. Journal of the American Statistical Association, 100, 484-492. Parzen, M.I., Wei, L.J. and Ying, Z. (1994). A resampling method based on pivotal estimating functions. Biometrika, 81, 341-350. Prentice, R.L. (1978). Linear rank tests with right censored data. Biometrika, 65, 167-179. Prentice, R.L. (1986). A case-cohort design for epidemiologic cohort studies and disease prevention trials. Biometrika, 73, 1-11. Sen, P.K. (1968). Estimates of the regression coefficient based on Kendall’s tau. Journal of the American Statistical Association, 63, 1379-1389. Shen, P.S. (2008). Nonparametric analysis of doubly truncated data. Journal of Statistical Planning and Inference, 138, 4041-4054. Stovring, H. and Wang, M.C. (2007). A new approach of nonparametric estimation of incidence and lifetime risk based on birth rates and incident events.BMC medical research, 7:53. Tsai, W. Y., Jewell, N. P. and Wang M. C. (1987). A note on the product-limit estimator under right censoring and left truncation. Biometrika, 74, 883-886. Tsai, W.Y. (1990). Testing the assumption of independence of truncation time and failure time. Biometrika, 77, 169-177. Tsai, W.Y. and Zhang, C.H. (1995). Asymptotic properties of nonparametric maximum likelihood estimator for interval-truncated data. Board of the Foundation of the Scandinavian Journal of Statistics, 22, 361-370. Tsiatis, A.A. (1990). Estimation regression parameters using linear rank tests for censored data. The Annals of Statistics, 18, 354-372. Turnbull, B.W. (1976). The empirical distribution function with arbitrarily grouped, censored and truncated data. Journal of the Royal Statistical Society. Series B, 38, 290-295. Ying, Z. (1993). A large sample study of rank estimation for censored regression data. The Annals of Statistics, 21, 76-99. 李世光(2007)在截切資料加速時間模式下的穩健排序估計方法。台灣大學流行病學研究所生物醫學統計組碩士論文。 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22857 | - |
| dc.description.abstract | 在許多臨床及公共衛生研究中經常會遇到雙截切資料，此資料只有當其事件發生在一段可觀察區段之間才會被觀察。本文考慮以一種可具體說明共變項與事件時間之間的線性關係之半母數加速事件時間模型來模式化其關係。基於上述的模式設定以及事件時間與可觀察區間的類獨立關係，本文發展出一種以U統計量為基礎的估計式以估計回歸係數。在本文所提出的估計方程式中，使用了可比較配對以調整雙截切所產生的偏誤。最後，進行模擬研究以檢視本文提出的方法在有限樣本下的表現。 | zh_TW |
| dc.description.abstract | In many clinical and public health studies, doubly truncated data are frequently encountered, in which the event of interest is observed only if it occurs in an observable interval. We consider a semi-parametrically accelerated failure time model which specifies a linear relationship between the event time and covariates. Based the above model setting and the quasi-independence assumption between event time and the observable interval, we develop a U-statistic-based estimating equation to estimate the regression coefficients. In our proposed estimating equation, comparable pairs are used to adjust the bias of double truncation. Finally, simulation studies are conducted to examine the performance of our proposed method in finite samples. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T04:30:56Z (GMT). No. of bitstreams: 1 ntu-98-R95842012-1.pdf: 324535 bytes, checksum: a3fd0801a647b35d3f1f93f0f70ff70c (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 第一章 導論 1
第一節 研究背景 1 第二節 研究動機 6 第二章 文獻回顧 9 第一節 COHORT-OF-CASES與個案世代研究之比較 9 第二節 截切資料與可比較配對 11 第三節 雙截切資料之回歸參數估計-加權最小平方法 13 第四節 一般化加權對數-排序檢定估計式 15 第五節 以U統計量為基礎的回歸參數估計式 17 第三章 方法 19 第四章 統計模擬 24 第一節 資料生成 24 第二節 模擬結果 26 第五章 結果與討論 27 參考文獻 28 附錄一 31 附錄二 33 附錄三 37 | |
| dc.language.iso | zh-TW | |
| dc.subject | 類獨立假設 | zh_TW |
| dc.subject | 雙截切資料 | zh_TW |
| dc.subject | U統計量 | zh_TW |
| dc.subject | 半母數加速事件時間模式 | zh_TW |
| dc.subject | 可比較配對 | zh_TW |
| dc.subject | U-statistic | en |
| dc.subject | Semi-parametric accelerated failure time model | en |
| dc.subject | Quasi-independence assumption | en |
| dc.subject | Comparable pair | en |
| dc.subject | Doubly-truncated data | en |
| dc.title | 探討雙截切資料之半母數加速事件時間模型的回歸參數估計 | zh_TW |
| dc.title | A semi-parametrically accelerated failure time model for doubly-truncated data | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳秀熙(Hsiu-Hsi Chen),戴政(Jen Tai),嚴明芳(Ming-Fang Yen) | |
| dc.subject.keyword | 雙截切資料,U統計量,半母數加速事件時間模式,可比較配對,類獨立假設, | zh_TW |
| dc.subject.keyword | Doubly-truncated data,U-statistic,Semi-parametric accelerated failure time model,Comparable pair,Quasi-independence assumption, | en |
| dc.relation.page | 39 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2009-11-30 | |
| 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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