Maximum likelihood analysis of semicompeting risks data with semiparametric regression models

Lifetime Data Analysis

Volumn 18, Issue 1, 2012, Pages 36-57

  Chen, Yi Hau ^a  

^a INSTITUTE OF STATISTICAL SCIENCE   (Taiwan)

Author keywords

Competing risks; Copula model; Dependent censoring; Informative censoring; Transformation model

Indexed keywords

ARTICLE; BONE MARROW TRANSPLANTATION; COMPUTER SIMULATION; HUMAN; LEUKEMIA; MORTALITY; RISK; STANDARD; STATISTICAL MODEL; TUMOR RECURRENCE;

BONE MARROW TRANSPLANTATION; COMPUTER SIMULATION; HUMANS; LEUKEMIA; LIKELIHOOD FUNCTIONS; MODELS, STATISTICAL; NEOPLASM RECURRENCE, LOCAL; RISK;

EID: 84855873449     PISSN: 13807870     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10985-011-9202-4     Document Type: Article

References (22)

1. Aalen OO (1977) Weak convergence of stochastic integrals related to counting process. Z Wahrsch verw Gebiete 38: 261-277.
2. Andersen PK, Borgan Ø, Gill R, Keiding N (1993) Statistical models based on counting processes. Springer, New York.
3. Chen YH (2009) Weighted Breslow-type and maximum likelihood estimation in semiparametric transformation models. Biometrika 96: 591-600.
4. Chen YH (2010) Semiparametric marginal regression analysis for dependent competing risks under an assumed copula. J Roy Stat Soc B 72: 235-251.
5. Coleman TF, Li Y (1994) On the convergence of reflective Newton methods for large-scale nonlinear minimization subject to bounds. Math Program 67: 189-224.
6. Coleman TF, Li Y (1996) An interior, trust region approach for nonlinear minimization subject to bounds. SIAM J Optim 6: 418-445.
7. Day R, Bryant J, Lefkopolou M (1997) Adaptation of bivariate frailty models for prediction, with application to biological markers as prognostic indicators. Biometrika 84: 45-56.
8. Ding AA, Shi G, Wang W, Hsieh JJ (2009) Marginal regression analysis for semicompeting risks data under dependent censoring. Scand J Stat 36: 481-500.
9. Fine JP, Jiang H, Chappell R (2001) On semicompeting risks data. Biometrika 88: 907-919.
10. Goethalsa K, Janssenb P, Duchateaua L (2008) Frailty models and copulas: similarities and differences. J Appl Stat 35: 1071-1079.
11. Hsieh JJ, Wang W, Ding AA (2008) Regression analysis based on semicompeting risks data. J Roy Stat Soc B 70: 3-20.
12. Huang X, Zhang N (2008) Regression survival analysis with an assumed copula for dependent censoring: a sensitivity analysis approach. Biometrics 64: 1090-1099.
13. Kalbfleisch JD, Prentice RL (2002) The Statistical analysis of failure time data, 2nd edn. Wiley, New York.
14. Klein JP, Moeschberger ML (2003) Survival analysis: techniques for censored and truncated data, 2nd edn. Springer, New York.
15. Nelsen RB (2006) An introduction to copulas, 2nd edn. Springer, New York.
16. Peng L, Fine JP (2007) Regression modeling of semicompeting risks data. Biometrics 63: 96-108.
17. Tsiatis A (1975) A nonidentifiability aspect of the problem of competing risks. Proc Natl Acad Sci USA 72: 20-22.
18. van der Vaart AW, Wellner JA (1996) Weak convergence and empirical processes. Springer, New York.
19. Wang W (2003) Estimating the association parameter for copula models under dependent censoring. J Roy Stat Soc B 65: 257-274.
20. Zeng D, Lin DY (2006) Efficient estimation of semiparametric transformation models for counting processes. Biometrika 93: 627-640.
21. Zeng D, Lin DY (2007) Maximum likelihood estimation in semiparametric regression models with censored data. J Roy Stat Soc B 69: 507-564.
22. Zheng M, Klein JP (1995) Estimates of marginal survival for dependent competing risks based on an assumed copula. Biometrika 82: 127-138.