删除或更新信息,请邮件至freekaoyan#163.com(#换成@)

带信息终止事件的复发事件数据的联合建模分析

本站小编 Free考研考试/2021-12-27

带信息终止事件的复发事件数据的联合建模分析 曹学锋1, 曲连强21. 黄冈师范学院数学系, 黄冈 438000;
2. 华中师范大学数学与统计学学院, 武汉 430079 Joint Modeling Analysis of Recurrent Event Data with Information Terminal Event CAO Xuefeng1, QU Lianqiang21. Department of Mathematics, Huanggang Normal University, Huanggang 438000, China;
2. College of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China
摘要
图/表
参考文献(0)
相关文章(9)
点击分布统计
下载分布统计
-->

全文: PDF(361 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)
摘要在本文中,我们利用联合建模方法,分析了带有信息终止事件的复发事件数据.对复发事件过程和终止事件过程,我们分别构造了可加比率和风险率模型,并引入一个共用的不可观测的脆弱变量刻画复发事件过程与终止事件过程的相依性.利用广义估计方程的方法,对模型参数进行了估计;并给出了所得估计的大样本性质.
服务
加入引用管理器
E-mail Alert
RSS
收稿日期: 2017-01-18
PACS:O212.7
引用本文:
曹学锋, 曲连强. 带信息终止事件的复发事件数据的联合建模分析[J]. 应用数学学报, 2017, 40(4): 530-542. CAO Xuefeng, QU Lianqiang. Joint Modeling Analysis of Recurrent Event Data with Information Terminal Event. Acta Mathematicae Applicatae Sinica, 2017, 40(4): 530-542.
链接本文:
http://123.57.41.99/jweb_yysxxb/CN/ http://123.57.41.99/jweb_yysxxb/CN/Y2017/V40/I4/530


[1] Cook R, Lawless J. The Statistical Analysis of Recurrent Events. New York:Springer, 2007
[2] Andersen P, Gill R. Cox's regression model for counting processes:a large sample study. Annals of Statistics, 1982, 10:1100-1120
[3] Lin D, Wei L, Yang I, Ying Z. Semiparametric regression for the mean and rate function of recurrent events. Journal of the Royal Statistical Society B, 2000, 62:711-730
[4] Lin D, Wei L, Ying Z. Semiparametric transformation models for point processes. Journal of the American Statistical Association, 2001, 96:620-628
[5] Zeng D, Lin D. Semiparametric transformation models with random effects for recurrent events. Journal of the American Statistical Association, 2007, 102:167-180
[6] Cook R, Lawless J, Lakhal-Chaieb L, Lee K-A. Robust estimation of mean functions and treatment effects for recurrent events under event-dependent censoring and termination:Application to skeletal complications in cancer metastatic to bone. Journal of the American Statistical Association, 2009, 104:60-75
[7] Zeng D, Cai J. A semiparametric additive rate model for recurrent events with informative terminal event. Biometrika, 2010, 97:699-712
[8] Sun L, Zhao X, Zhou J. A class of mixed models for recurrent event data. The Canadian Journal of Statistics, 2011, 39:578-590
[9] Kalbfleisch J, Prentice R. The Statistical Analysis of Failure Time Data, 2nd edition. New York:Wiley, 2002
[10] Pan Q, Schaubel D. Flexible estimation of differences in treatment-specific recurrent event means in the presence of a terminating event. Biometrics, 2009, 65:753-761
[11] Liu D, Schaubel D, Kalbfleisch J. Computationally efficient marginal models for clustered recurrent event data. Biometrics, 2012, 68:637-647
[12] Wang M C, Qin J, Chiang C. Analyzing recurrent event data with informative censoring. Journal of the American Statistical Association, 2001, 96:1057-1065
[13] Liu L, Wolfe R, Huang X. Shared frailty model for recurrent events and a terminal event. Biometrics, 2004, 60:747-756
[14] Huang C Y, Wang M C. Joint modeling and estimation for recurrent event processes and failure time data. Journal of the American Statistical Association, 2004, 99:1153-1165
[15] Zeng D, Lin D. Semiparametric transformation models with random effects for joint analysis of recurrent and terminal events. Biometrics, 2009, 65:746-752
[16] Ghosh D, Lin D. Marginal regression models for recurrent and terminal events. Statistica Sinica, 2002, 12:663-688
[17] Schaubel D, Zhang M. Estimating treatment effects on the marginal recurrent event mean in the presence of a terminating event. Lifetime Data Analysis, 2010, 16:451-477
[18] Zhao X, Zhou J, Sun L. Semiparametric transformation models with time-varying coefficients for recurrent and terminal events. Biometrics, 2011, 67:404-414
[19] Kalbfleisch J, Schaubel D, Ye Y, Gong Q. An estimating function approach to the analysis of recurrent and terminal events. Biometrics, 2013, 69:366-374
[20] Cook R, Lawless J. Marginal analysis of recurrent events and a terminating event. Statistics in Medicine, 1997, 16:911-924
[21] Ye Y, Kalbfleisch J, Schaubel D. Semiparametric analysis of correlated recurrent and terminal events. Biometrics, 2007, 63:78-87
[22] Sun L, Kang F. An additive-multiplicative rates model for recurrent event data with informative terminal event. Lifetime Data Analysis, 2013, 19:117-137
[23] Chen C M, Shen P S, Chuang Y W. The partly Aalen s model for recurrent event data with a dependent terminal event. Statistics in Medicine, 2016, 35:268-281
[24] Schaubel D, Zeng D, Cai J. A semiparametric additive rates model for recurrent event data. Lifetime Data Analysis, 2006, 12:389-406
[25] Lin D, Ying Z. Semiparametric analysis of the additive risk model. Biometrika, 1994, 81:61-71
[26] Lin D, Wei L, Ying Z. Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika, 1993, 80:557-572
[27] Pollard D. Empirical Processes:Theory and Applications. Institute of Mathematical Statistics, Hayward, CA, 1990
[28] Rudin W. Principles of Mathematical Analysis, 3nd edition. New York:McGraw-Hill, 1976
[29] Lin F, Cai J, Fine J, Lai H. Nonparametric estimation of the mean function for recurrent event data with missing event category. Biometrika, 2013, 100:727-740
[30] van der Vaart A, Wellner J. Weak Convergence and Empirical Processes. New York:Springer, 1996

[1]郦博文, 张海祥. 多类型复发事件数据下一类Box-Cox转移模型[J]. 应用数学学报, 2016, 39(5): 656-668.
[2]马燕, 裴艳波, 张海祥. 多类型的复发事件数据下一类混合模型[J]. 应用数学学报, 2015, 38(4): 660-672.
[3]戴家佳, 关楷谕, 吴欢. 带有终止事件的复发事件数据的加性加速比率模型[J]. 应用数学学报, 2015, 38(4): 735-750.
[4]苗瑞, 李怿. 有偏抽样下带终止时间和带信息观察时间的纵向数据分析[J]. 应用数学学报(英文版), 2013, 36(6): 961-977.
[5]何穗, 程希明, 周洁. 带终止事件的多类型复发事件的一般加性乘积比例模型[J]. 应用数学学报(英文版), 2012, 35(5): 804-816.
[6]何穗, 王芬. 成组复发事件下的半参数变换模型[J]. 应用数学学报(英文版), 2012, (4): 728-736.
[7]何穗, 王芬, 刘焕彬. 成组复发事件下的一般半参数加性乘积比率回归模型[J]. 应用数学学报(英文版), 2010, 33(3): 412-423.
[8]张忠占. 使用Mantel-Haenszel方法在套情形控制研究中估计风险比率[J]. 应用数学学报(英文版), 2001, 17(4): 457-468.
[9]张忠占. 使用Mantel-Haenszel方法在套情形控制研究中估计风险比率[J]. 应用数学学报(英文版), 2001, 17(4): 457-468.



PDF全文下载地址:

http://123.57.41.99/jweb_yysxxb/CN/article/downloadArticleFile.do?attachType=PDF&id=14346
相关话题/应用数学 数据 信息 过程 统计