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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 江金倉 | |
| dc.contributor.author | Chi-Hua Wang | en |
| dc.contributor.author | 王啟樺 | zh_TW |
| dc.date.accessioned | 2021-06-15T13:10:10Z | - |
| dc.date.available | 2026-06-27 | |
| dc.date.copyright | 2016-07-04 | |
| dc.date.issued | 2016 | |
| dc.date.submitted | 2016-06-28 | |
| dc.identifier.citation | Buckley, J. and James, I. (1979). Linear regression with censored data. Biometrika. 66, 429-436.
Berkson, J. and Gage, R. P. (1952). Survival curve for cancer patients following treatment. J. Amer. Statist. Assoc. 47, 501-515. 11 Chen, M. H. , Ibrahim, J. G., and Sinha, D. (1999). A new Bayesian model for survival data with a surviving fraction. J. Amer. Statist. Assoc. 94, 909-919. Dabrowska, D. M., and Doksum, K. A. (1952). Estimation and Testing in the Two-Sample Generalized Odds-Rate Model. J. Amer. Statist. Assoc. 83, 744-749. Farewell, V. T. (1982). The use of mixture models for the analysis of survival data with long-term survivors. Biometrics. 38, 1041-1046. Kim, S., Xi, Y., and Chen, M. H.(2009). A new latent cure rate marker model for survival data. Ann. Appl. Stat. 3, 1124-1146. Kuk, A. Y. C. and Chen, C. H. (1992). A mixture model combining logistic regression with proportional hazards regression. Biometrika. 79, 531-541. Mao, M. and Wang, J.L. (2010). Semiparametric efficient estimation for a class of generalized proportional odds cure models. J. Amer. Statist. Assoc. 105, 302-311. Peng, Y., Dear, K. B. G., and Denham J. W.(1998). A generalized F mixture model for cure rate estimation. Stat. Med. 17, 813-830. Sy, J. P. and Taylor, J. M. G. (2000). Estimation in a Cox proportional hazards cure model. Biometrics 56, 227-236. Tsodikov, A. (1998). A proportional hazards model taking account of long-term survivors. Biometrics. 54, 1508-1516. Yakovlev, A.Y., Asselain, B., Bardou, V. J., Fourquet, A., Hoang, T., Rochefediere, A., and Tsodikov, A. D. (1993). A Simple Stochastic Model of Tumor Recurrence and Its Appli- cations to Data on pre-menopausal Breast Cancer. In Biometrie et Analyse de Dormees Spatio Temporelles, 12 (Eds. B. Asselain, M. Boniface, C. Duby, C. Lopez, J.P.Masson, and J.Tranchefort). Socit Francaise de Biomtrie, ENSA Renned, France, 66-82. Yakovlev, A. Y. and Tsodikov, A. D. (1996). Stochastic Models of Tumor La- tency and Their Biostatistical Applications, Singapore: World Scientific. Yin, G. and Ibrahim, J. G. (2005). Cure rate models: a unified approach. Can. J. Stat. 33, 559-570. Zeng, D., Yin, G., and Ibrahim, J. G. (2006). Semiparametric transformation models for survival data with a cure fraction. J. Amer. Statist. Assoc. 101, 670-684. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/50976 | - |
| dc.description.abstract | 對於包含治癒情形的存活資料，本文章提出更一般的半參數併發時間治癒模型，不但具有對於癌症併發機制的生物意義，更同時包含比例風險模式與比例贏輸比模式。當中提出的指標係數的擬積分最小平方估計式具有一致性以及漸進常態性，計算面上更提供有效率的演算法。另外對於併發時間函數之估計，給出擬最小平方估計與動差估計兩種形式。對於提出的估計式，我們執行了豐富的數值模擬去檢驗其在有限樣本下的表現。 | zh_TW |
| dc.description.abstract | For survival data with a cure fraction, we propose a general semiparametric model which is derived from the biological process of cancer-relapse mechanism and includes both the mixture cure models and promotion time cure models as two special cases. The pseudo integrated least squares estimators (PILSEs) of index coefficients are shown to be consistent and asymptotically normal and
an efficient computing algorithm is proposed to calculate the PILSEs of index coefficients and the moment-type estimators of promotion time function. Simulation studies are conducted to examine the finite-sample properties of the proposed estimators. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T13:10:10Z (GMT). No. of bitstreams: 1 ntu-105-R03246008-1.pdf: 2284820 bytes, checksum: 97cfe721a89c8778fd25af928ae5b901 (MD5) Previous issue date: 2016 | en |
| dc.description.tableofcontents | 1 Introduction (1)
2 Estimation (5) 2.1 Background (6) 2.2 Estimation of Index Coefficients (7) 2.3 Estimation of Promotion Time Function (9) 3 Large Sample Properties (11) 3.1 Asymptotic Normality of Coefficient Estimators (11) 4. Monte Carlo Simulations (15) 5 Reference (18) A Appendix (20) | |
| dc.language.iso | en | |
| dc.subject | 一致性 | zh_TW |
| dc.subject | 漸進常態 | zh_TW |
| dc.subject | 併發時間治癒模型 | zh_TW |
| dc.subject | 單指標存活模型 | zh_TW |
| dc.subject | 單指標存活模型 | zh_TW |
| dc.subject | 一致性 | zh_TW |
| dc.subject | 漸進常態 | zh_TW |
| dc.subject | 併發時間治癒模型 | zh_TW |
| dc.subject | promotion time cure model | en |
| dc.subject | asymptotic normality | en |
| dc.subject | consistency | en |
| dc.subject | single-index survival model | en |
| dc.subject | promotion time cure model | en |
| dc.subject | asymptotic normality | en |
| dc.subject | consistency | en |
| dc.subject | single-index survival model | en |
| dc.title | 併發時間治癒模型之估計 | zh_TW |
| dc.title | Estimation of a General Semiparametric Promotion Time Cure Model | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 104-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 黃禮珊,鄭又仁 | |
| dc.subject.keyword | 漸進常態,一致性,單指標存活模型,併發時間治癒模型, | zh_TW |
| dc.subject.keyword | asymptotic normality,consistency,single-index survival model,promotion time cure model, | en |
| dc.relation.page | 42 | |
| dc.identifier.doi | 10.6342/NTU201600515 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2016-06-28 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 應用數學科學研究所 | zh_TW |
| 顯示於系所單位： | 應用數學科學研究所 | |
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