A general additive-multiplicative rates model for recurrent event data

Science in China, Series A: Mathematics

Volumn 52, Issue 10, 2009, Pages 2257-2265

  Dai, Jia Jia ^a,b   Sun, Liu Quan ^c   Yang, Zhen Hai ^b  

^a GUIZHOU UNIVERSITY   (China)

^b BEIJING UNIVERSITY OF TECHNOLOGY   (China)

^c INSTITUTE OF APPLIED MATHEMATICS   (China)

Author keywords

Counting process; Generalized estimating equation; Marginal model; Recurrent event

Indexed keywords

EID: 70350330165     PISSN: 10069283     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11425-009-0095-6     Document Type: Article

References (18)

1. Wei L J, Lin D Y, Weissfeld L. Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. J Amer Statist Assoc, 84: 1065-1073 (1989).
2. Lee E W, Wei L J, Amato D A. Cox-type regression analysis for large numbers of small groups of correlated failure time observations. In: Klein J P, Goel P K, eds. Survival Analysis: State of the Art. Dordrecht: Kluwer, 1992, 237-247.
3. Prentice R L, Williams B J, Peterson A V. On the regression analysis of multivariate failure time data. Biometrika, 68: 373-379 (1981).
4. Andersen P K, Gill R D. Cox's regression model for counting processes: A large sample study. Ann Statist, 10: 1100-1120 (1982).
5. Chang S H, Wang M C. Conditional regression analysis for recurrence time data. J Amer Statist Assoc, 94: 1221-1230 (1999).
6. Wang M C, Chen Y Q. Nonparametric and semiparametric trend analysis for stratified recurrence time data. Biometrics, 56: 789-794 (2000).
7. Schaubel D E, Zeng D L, Cai J W. A semiparametric additive rates model for recurrent event data. Lifetime Data Anal, 12: 389-406 (2006).
8. Lin D Y, Wei L J, Yang I, et al. Semiparametric regression for the mean and rate functions of recurrent events. J Roy Statist Soc Ser B, 62(4): 711-730 (2000).
9. Lin D Y, Wei L J, Ying Z. Semiparametric transformation models for point processes. J Amer Statist Assoc, 96: 620-628 (2001).
10. Cai J, Schaubel D E. Marginal means/rates models for multiple type recurrent event data. Lifetime Data Anal, 10: 121-138 (2004).
11. Pepe M S, Cai J. Some graphical displays and marginal regression analyses for recurrent failure times and time-dependent covariates. J Amer Statist Assoc, 88: 811-820 (1993).
12. Lawless J F, Nadeau C. Some simple robust methods for the analysis of recurrent events. Technometrics, 37: 158-168 (1995).
13. Lawless J F, Nadeau C, Cook R J. Analysis of mean and rate functions for recurrent events. In: Proc 1st Seattle Symp Biostatistcs: Survival Analysis. New York: Springer, 1997, 37-49.
14. Lin D Y, Ying Z L. Semiparametric analysis of the additive risk model. Biometrika, 81(1): 61-71 (1994).
15. Fleming T R, Harrington D P. Counting Processes and Survival Analysis. New York: Wiley, 1991.
16. Byar D P. The Veterans Administration study of chemoprophylaxis for recurrent stage I bladder tumors: Comparisons of placebo, pyridoxine, and topical thitepa. In: Pavone-Macaluso M, Smith P H, Edsmyn F, eds. Bladder Tumors and Other Topics in Urological oncology. New York: Plenum Press, 1980, 363-370.
17. Lin D Y, Ying Z L. Semiparametric analysis of general additive-multiplicative hazard models for counting processes. Ann Statist, 23(5): 1712-1734 (1995).
18. Pollard D. Empirical Processes: Theory and Applications. Hayward: Institute of Mathematical Statistics, 1990.