期刊文献+

The Additive-multiplicative Hazards Model for Multiple Type of Recurrent Gap Times

The Additive-multiplicative Hazards Model for Multiple Type of Recurrent Gap Times
下载PDF
导出
摘要 Recurrent event gap times data frequently arise in biomedical studies and often more than one type of event is of interest. To evaluate the effects of covariates on the marginal recurrent event hazards functions, there exist two types of hazards models: the multiplicative hazards model and the additive hazards model. In the paper, we propose a more flexible additive-multiplicative hazards model for multiple type of recurrent gap times data, wherein some covariates are assumed to be additive while others are multiplicative. An estimating equation approach is presented to estimate the regression parameters. We establish asymptotic properties of the proposed estimators. Recurrent event gap times data frequently arise in biomedical studies and often more than one type of event is of interest. To evaluate the effects of covariates on the marginal recurrent event hazards functions, there exist two types of hazards models: the multiplicative hazards model and the additive hazards model. In the paper, we propose a more flexible additive-multiplicative hazards model for multiple type of recurrent gap times data, wherein some covariates are assumed to be additive while others are multiplicative. An estimating equation approach is presented to estimate the regression parameters. We establish asymptotic properties of the proposed estimators.
出处 《Communications in Mathematical Research》 CSCD 2015年第2期97-107,共11页 数学研究通讯(英文版)
基金 The Science Foundation(JA12301)of Fujian Educational Committee the Teaching Quality Project(ZL0902/TZ(SJ))of Higher Education in Fujian Provincial Education Department
关键词 additive-multiplicative hazards model estimating equation gap time multiple recurrent event data semi-parametric regression model additive-multiplicative hazards model, estimating equation, gap time,multiple recurrent event data, semi-parametric regression model
  • 相关文献

参考文献23

  • 1Prentice R L, Williams B J, Peterson A V. On the regression analysis of multivariate failure time data. Biometrika, 1981, 68: 373-379.
  • 2Andersen P K, Gill R D. Cox's regression model for counting processes: a large sample study, Ann. Statist., 1982, I0: 1100-1120.
  • 3Zeng D, Lin D. Efficient estimation of semiparametrie transformation models for counting processes. Biometrika, 2006, 93: 627-640.
  • 4Pepe M S, Cai J. Some graphical displays and marginal regression analyses for recurrent failure times and time dependent covariates. J. Amer. Statist. Assoc., 1993, 88: 811-820.
  • 5Lin D, Wei L, Ying Z. Semiparametric regression for the mean and rate functions of recurrent events. J. Roy. Statist. Soc. Set. B, 2000, 62: 711-730.
  • 6Nielsen G G, Gill R D, Andersen P K, Sorensen T. A counting process approach to maximum likelihood estimation in frailty models. Scand. J. Statist., 1992, 19: 25-43.
  • 7Zeng D, Lin D Y. Semiparametric transformation models with random effects for recurrent events. J. Amer. Statist. Assoc., 2007, 102: 167-180.
  • 8Zeng D, Lin D Y. Semiparametric transformation models with random effects for joint analysis of recurrent and terminal event. Biometrics, 2009, 65: 746-752.
  • 9Spiekman C F, Lin D Y. Marginal regression models for multivariate failure tie data. J. Amer. Statist. Assoc., 1998, 93: 1164-1175.
  • 10Clegg L X, Cai J, Sen P K. A marginal mixed baseline hazards model for multivariate failure time data. Biometrics, 1999, 55: 805-812.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部