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題名 雙變量脆弱性韋伯迴歸模式之研究 作者 余立德
Yu, Li-Ta貢獻者 陳麗霞
余立德
Yu, Li-Ta關鍵詞 雙變量脆弱性
Weibull迴歸模式
對數常態分配
EM法則
bivariate frailty
Weibull regression model
log-normal distribution
EM algorithm日期 1998 上傳時間 21-Apr-2016 09:55:08 (UTC+8) 摘要 摘要
Abstract參考文獻 參考文獻[1] Aalen, O. O., (1988). "Heterogeneity in Survival Analysis",Statistics in medicine, vol. 7, p. 1121-1137.[2] Aalen, O. O., (1992). "Modeling Heterogeneity in SurvivalAnalysis by the compound Poisson distribution", Ann. Appl. Prob.,vol. 2, p. 951- 972.[3] Clayton, D. G., (1978). "A Model for Association in Bivariate LifeTables and Its Application in Epidemiological Studies of FamilialTendency in Chronic Disease Incidence", Biometrika, vol. 65, p.141-151.[4] Clayton, D. G., and Cuzick, J., (1985). "Multivariate Associations ofThe Proportional Hazards Model", Journal of the Royal StatisticalSociety, Ser. A vol. 148, p. 82-108.[5] Clayton, D. G., (1991). "A Monte Carlo Method for BinaryInference in Frailty Models", Biometrics, vol. 47, p. 467-485.[6] Gail, M. H., Wieand, S. and Piantados, S., (1984). "BiasedEstimates of Treatment Effect in Randomized Experiments withNonlinear Regression and Omitted Covariates", Biometrika, vol. 71,p. 431-444.[7] Gilks, W. R., Best, N. G., Tan, K. K. C., (1995). "Adaptive RejectionMetropolis Sampling within Gibbs Sampling", Applied Statistics,vol. 44., p.455-472.[8] Hougaard, P., (1986). "Survival Models for HeterogeneousPopulations Derived from Stable Distributions", Bimoetrika, vol. 73,p. 387-396.[9] Hougaard, P., (1986). "A Class of Multivariate Failure TimeDistributions ", Bimoetrika, vol. 73, p. 671-678.[10] Huster, W. J., Brookmeyer, R., and Self,,S. G., (1989). "ModelingPaired Survival Data with Covariates", Biometrics, vol. 45, p. 145-156.[11] Klein, J. P., and Moeschberger, M. I., (1988). "Bounds on NetSurvival Probabilities for Dependent Competing Risks",Biometrics, vol. 44 ,p. 529-538.[12] Lancaster, T., (1990). The Econometrics Analysis of Transition Data.CUP, Cambridge.[13] Lindley, D. V., and Singpurwalla, N. D., (1986). "MultivariateDistributions for the Life Lengths of Components of a SystemSharing a Common Environment", Journal of Applied Probability,vol. 23, p. 418-431.[14] Mcgilchrist, A., and Aisbett, C. W., (1991). "Regression with Frailtyin Survival Analysis", Biometrics, vol. 47, p. 461-466.[15] Pickles, A., and Crouchley, R., (1995). "A Comparison of FrailtyModels for Multivariate Survival Data", Statistics in Medicine, vol.14, p. 1447-1461.[16] Wei, L. J., Lin, D. Y., and Weissfeld, L., (1989). "RegressionAnalysis of Multivariate Incomplete Failure Time Data byModeling Marginal Distributions", Journal of the AmericanStatistical Association, vol. 84, p. 1065-1073.[17] Wei, G. C. G., Tanner, M. A., (1990). "A Monte CarloImplementation of the EM algorithm and the Poor Man`s DataAugmentation Algorithms", Journal of the American StatisticalAssociation, vol. 85, p. 699-704.[18] Xue, X., (1995). Analysis of Survival Data under Heterogeneity:Univariate and Bivariate Frailty Models. Unpublished Ph.D. Thesis,School of Hygiene and Public Health, Johns Hopkins University.[19] 陳麗霞, (民84). "脆弱性Weibull迴歸模式之貝氏推論".國科會計畫, NSC-84-2415-H-004-006. 描述 碩士
國立政治大學
統計學系
86354003資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002001563 資料類型 thesis dc.contributor.advisor 陳麗霞 zh_TW dc.contributor.author (Authors) 余立德 zh_TW dc.contributor.author (Authors) Yu, Li-Ta en_US dc.creator (作者) 余立德 zh_TW dc.creator (作者) Yu, Li-Ta en_US dc.date (日期) 1998 en_US dc.date.accessioned 21-Apr-2016 09:55:08 (UTC+8) - dc.date.available 21-Apr-2016 09:55:08 (UTC+8) - dc.date.issued (上傳時間) 21-Apr-2016 09:55:08 (UTC+8) - dc.identifier (Other Identifiers) B2002001563 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/85892 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 統計學系 zh_TW dc.description (描述) 86354003 zh_TW dc.description.abstract (摘要) 摘要 zh_TW dc.description.abstract (摘要) Abstract en_US dc.description.tableofcontents 目錄第一章 緒論……………………………………… 11-1節 研究動機與目的………………………………11-2節 文獻回顧………………………………………41-3節 論文架構………………………………………5第二章 雙變量存活時間之相關係數………………62-1節 具有雙變量脆弱性的雙變量存活模式………62-2節 條件存活時間為韋伯(Weibull)及指數(exponential)分配時的相關係數………………… 7第三章 具有雙變量脆弱性的多變量存活模式之估計…………………………………………213-1節 雙變量存活資料………………………… 213-1-1節 對數脆弱性為部分相關的雙變量存活資料…………………………………………213-1-2節 對數脆弱性為完全相關的雙變量存活資料…………………………………………303-2節 多變量存活資料……………………………333-2-1節 對數脆弱性為部分相關的多變量存活資料…………………………………………333-2-2節 對數脆弱性為完全相關的多變量存活資料…………………………………………37第四章 模擬與計算……………………………….…414-1節 蒙地卡羅EM法則(MCEM)……………………414-2 節 模擬研究…………………………………… 42第五章 結論與建議……………………………… 51參考文獻…………………………………………… 53附錄………………………………………………… 55 zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002001563 en_US dc.subject (關鍵詞) 雙變量脆弱性 zh_TW dc.subject (關鍵詞) Weibull迴歸模式 zh_TW dc.subject (關鍵詞) 對數常態分配 zh_TW dc.subject (關鍵詞) EM法則 zh_TW dc.subject (關鍵詞) bivariate frailty en_US dc.subject (關鍵詞) Weibull regression model en_US dc.subject (關鍵詞) log-normal distribution en_US dc.subject (關鍵詞) EM algorithm en_US dc.title (題名) 雙變量脆弱性韋伯迴歸模式之研究 zh_TW dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 參考文獻[1] Aalen, O. O., (1988). "Heterogeneity in Survival Analysis",Statistics in medicine, vol. 7, p. 1121-1137.[2] Aalen, O. O., (1992). "Modeling Heterogeneity in SurvivalAnalysis by the compound Poisson distribution", Ann. Appl. Prob.,vol. 2, p. 951- 972.[3] Clayton, D. G., (1978). "A Model for Association in Bivariate LifeTables and Its Application in Epidemiological Studies of FamilialTendency in Chronic Disease Incidence", Biometrika, vol. 65, p.141-151.[4] Clayton, D. G., and Cuzick, J., (1985). "Multivariate Associations ofThe Proportional Hazards Model", Journal of the Royal StatisticalSociety, Ser. A vol. 148, p. 82-108.[5] Clayton, D. G., (1991). "A Monte Carlo Method for BinaryInference in Frailty Models", Biometrics, vol. 47, p. 467-485.[6] Gail, M. H., Wieand, S. and Piantados, S., (1984). "BiasedEstimates of Treatment Effect in Randomized Experiments withNonlinear Regression and Omitted Covariates", Biometrika, vol. 71,p. 431-444.[7] Gilks, W. R., Best, N. G., Tan, K. K. C., (1995). "Adaptive RejectionMetropolis Sampling within Gibbs Sampling", Applied Statistics,vol. 44., p.455-472.[8] Hougaard, P., (1986). "Survival Models for HeterogeneousPopulations Derived from Stable Distributions", Bimoetrika, vol. 73,p. 387-396.[9] Hougaard, P., (1986). "A Class of Multivariate Failure TimeDistributions ", Bimoetrika, vol. 73, p. 671-678.[10] Huster, W. J., Brookmeyer, R., and Self,,S. G., (1989). "ModelingPaired Survival Data with Covariates", Biometrics, vol. 45, p. 145-156.[11] Klein, J. P., and Moeschberger, M. I., (1988). "Bounds on NetSurvival Probabilities for Dependent Competing Risks",Biometrics, vol. 44 ,p. 529-538.[12] Lancaster, T., (1990). The Econometrics Analysis of Transition Data.CUP, Cambridge.[13] Lindley, D. V., and Singpurwalla, N. D., (1986). "MultivariateDistributions for the Life Lengths of Components of a SystemSharing a Common Environment", Journal of Applied Probability,vol. 23, p. 418-431.[14] Mcgilchrist, A., and Aisbett, C. W., (1991). "Regression with Frailtyin Survival Analysis", Biometrics, vol. 47, p. 461-466.[15] Pickles, A., and Crouchley, R., (1995). "A Comparison of FrailtyModels for Multivariate Survival Data", Statistics in Medicine, vol.14, p. 1447-1461.[16] Wei, L. J., Lin, D. Y., and Weissfeld, L., (1989). "RegressionAnalysis of Multivariate Incomplete Failure Time Data byModeling Marginal Distributions", Journal of the AmericanStatistical Association, vol. 84, p. 1065-1073.[17] Wei, G. C. G., Tanner, M. A., (1990). "A Monte CarloImplementation of the EM algorithm and the Poor Man`s DataAugmentation Algorithms", Journal of the American StatisticalAssociation, vol. 85, p. 699-704.[18] Xue, X., (1995). Analysis of Survival Data under Heterogeneity:Univariate and Bivariate Frailty Models. Unpublished Ph.D. Thesis,School of Hygiene and Public Health, Johns Hopkins University.[19] 陳麗霞, (民84). "脆弱性Weibull迴歸模式之貝氏推論".國科會計畫, NSC-84-2415-H-004-006. zh_TW