Centre-effect on survival after bone marrow transplantation: Application of time-dependent frailty models

Biometrical Journal

Volumn 46, Issue 5, 2004, Pages 512-525

  Wintrebert, Claire M A ^a   Putter, Hein ^a   Zwinderman, Aeilko H ^b   Van Houwelingen, J C ^a  

^a LEIDEN UNIVERSITY MEDICAL CENTER   (Netherlands)

^b ACADEMIC MEDICAL CENTER   (Netherlands)

Author keywords

Centre effect; Multivariate failure time; Time varying frailty

Indexed keywords

BIOMEDICAL INVESTIGATIONS; BONE MARROW TRANSPLANTATION; CENTER-EFFECT; FAILURE TIME; FAILURE TIME DATA; FRAILTY MODELS; MULTIVARIATE FAILURE TIME; TIME DEPENDENT; TIME VARYING; TIME-VARYING FRAILTY;

EID: 19644400880     PISSN: 03233847     EISSN: None     Source Type: Journal    
DOI: 10.1002/bimj.200310051     Document Type: Article

References (20)

1. Abramowitz, M. and Stegun, I. (1965). Handbook of Mathematical Functions. Dovers Publications, New-York.
2. Andersen, P. K., Mein, J. P., and Zhang, M. (1999). Testing for centre effects in multi-centre survival studies: a Monte Carlo comparison of fixed and random effects tests. Statistics in Medicine 18, 1489-1500.
3. Breslow, N. (1974). Covariance analysis of censored survival data. Biometrics 30, 89-100.
4. Clayton, D. G. (1978). A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika 65, 141-151.
5. Clayton, D. G. and Cuzick, J. (1985). Multivariate generalizations of the proportional hazards model (with discussion). Journal of the Royal Statistical Society, Series A 148, 82-117.
6. Ducrocq, V. and Casella, G. (1996). A bayesian analysis of mixed survival models. Genetics, Selection, Evolution 28, 505-529.
7. Hougaard, P. (2000). Analysis of Multivariate Survival Data. Springer-Verlag, New-York.
8. Kaplan, E. L. and Meier, P. (1958). Nomparametric estimation from incomplete observations. Journal of the American Statistical Association 53, 457-481.
9. Klein, J. and Moeschberger, M. (1997). Survival Analysis - Techniques for Censored and Truncated Data. Statistics for biology and health. Springer-Verlag, New-York.
10. Korsgaard, I., Madsen, P., and Jensen, J. (1998). Bayesian inference in the semiparametric log normal frailty model using Gibbs sampling. Genetics, Selection, Evolution 30, 241-256.
11. Lindeboom, M. and van der Berg, G. J. (1994). Heterogeneity in models for bivariate survival: the importance of the mixing distribution. Journal of the Royal Statistical Society, Series B 56, 49-60.
12. Oakes, D. (1982). A model for association in bivariate survival data. Journal of the Royal Statistical Society, Series B 44, 414-422.
13. Oakes, D. (1989). Bivariate survival models induced by frailties. Journal of the American Statistical Association 84, 487-493.
14. Paik, M., Tsai, W.-Y., and Ottman, R. (1994). Multivariate survival analysis using piecewise gamma frailty. Biometrics 50, 975-988.
15. Press, W., Teukolsky, S., Vetterling, W., and Flannery, B. (1992). Numerical Recipes in C. Cambridge University Press, Cambridge, second edition.
16. Ripatti, S. and Palmgren, J. (2000). Estimation of multivariate frailty models using penalized partial likelihood. Biometrics 56, 1016-1022.
17. Smits, J., Meester, J. D., Deng, M. C., Scheld, H. H., Hummel, M., Schoendube, F., Haverich, A., Vanhaecke, J., and van Houwelingen, J. (2003). Mortality rates after heart transplantation: How to compare center-specific outcome data? Transplantation 75, 90-96.
18. Smits, J., van Houwelingen, J., Meester, J. D., le Cessie, S., Persijn, G., Claas, F., and Frei, U. (2000). Permanent detrimental effect of non immunological factors on long-term renal graft survival. A parsimonious model of time-dependency. Transplantation 70, 317-323.
19. Vaida, F. and Xu, R. (2000). Proportional hazards model with random effects. Statistics in Medicine 19, 3309-3324.
20. Verweij, P. and van Houwelingen, J. (1995). Time-dependent effects of fixed covariates in Cox regression. Biometrics 51, 1550-1556.