A New Bayesian Model for Survival Data with a Surviving Fraction

Journal of the American Statistical Association

Volumn 94, Issue 447, 1999, Pages 909-919

  Chen, Ming Hui ^a   Ibrahim, Joseph G ^b   Sinha, Debajyoti ^c  

^a Worcester Polytechnic Institute   (United States)

^b DANA FARBER CANCER INSTITUTE   (United States)

^c Univ of New Hampshire   (United States)

Author keywords

Cure rate model; Gibbs sampling; Historical data; Latent variables; Posterior distribution; Weibull distribution

Indexed keywords

EID: 1542427732     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1080/01621459.1999.10474196     Document Type: Article

References (24)

1. Berkson, J., and Gage, R. P. (1952), "Survival Curve for Cancer Patients Following Treatment, " Journal of the American Statistical Association, 47, 501-515.
2. Chen, M-H., Ibrahim, J. G., and Yiannoutsos, C. (1999), "Prior Elicitation, Variable Selection, and Bayesian Computation for Logistic Regression Models, " Journal of the Royal Statistical Society, Ser. B, 61, 223-242.
3. Chen, M-H., and Shao, Q-M. (1999), "Monte Carlo Estimation of Bayesian Credible and HPD Intervals, " Journal of Computational and Graphical Statistics, 8, 69-92.
4. Diaconis, P., and Ylvisaker, D. (1979), "Conjugate Priors for Exponential Families, " The Annals of Statistics, 7, 269-281.
5. Ewell, M., and Ibrahim, J. G. (1997), "The Large Sample Distribution of the Weighted Log Rank Statistic Under General Local Alternatives, " Lifetime Data Analysis, 3, 5-12.
6. Farewell, V. T. (1982), "The Use of Mixture Models for the Analysis of Survival Data With Long-Term Survivors, " Biometrics, 38, 1041-1046.
7. Farewell, V. T. (1986), "Mixture Models in Survival Analysis: Are They Worth the Risk?" Canadian Journal of Statistics, 14, 257-262.
8. Gilks, W. R., and Wild, P. (1992), "Adaptive Rejection Sampling for Gibbs Sampling, " Applied Statistics, 41, 337-348.
9. Goldman, A. I. (1984), "Survivorship Analysis When Cure is a Possibility: A Monte Carlo Study, " Statistics in Medicine, 3, 153-163.
10. Gray, R. J., and Tsiatis, A. A. (1989), "A Linear Rank Test for Use When the Main Interest is in Differences in Cure Rates, " Biometrics, 45, 899-904.
11. Greenhouse, J. B., and Wolfe, R. A. (1984), "A Competing Risks Derivation of a Mixture Model for the Analysis of Survival, " Communications in Statistics, Part A-Theory and Methods, 13, 3133-3154.
12. Halpern, J., and Brown, B. W., (1987a), "Cure Rate Models: Power of the Log Rank and Generalized Wilcoxon Tests, " Statistics in Medicine, 6, 483-489.
13. Halpern, J., and Brown, B. W (1987b), "Designing Clinical Trials With Arbitrary Specification of Survival Functions and for the Log Rank or Generalized Wilcoxon Test, " Controlled Clinical Trials, 8, 177-189.
14. Ibrahim, J. G., Ryan, L. M., and Chen, M-H. (1998), "Use of Historical Controls to Adjust for Covariates in Trend Tests for Binary Data, " Journal of the American Statistical Association, 93, 1282-1293.
15. Kirkwood, J. M., Strawderman, M. H., Ernstoff, M. S., Smith, T. J., Borden, E. c., and Blum, R. H. (1996), "Interferon Alfa-2b Adjuvant Therapy of High-Risk Resected Cutaneous Melanoma: The Eastern Cooperative Oncology Group Trial EST 1684, " Journal of Clinical Oncology, 14, 7-17.
16. Kuk, A. Y. c., and Chen, C-H. (1992), "A Mixture Model Combining Logistic Regression With Proportional Hazards Regression, " Biometrika, 79, 531-541.
17. Laska, E. M., and Meisner, M. J. (1992), "Nonparametric Estimation and Testing in a Cure Rate Model, " Biometrics, 48, 1223-1234.
18. Morris, C. N. (1982), "Natural Exponential Families With Quadratic Variance Functions, " The Annals of Statistics, 10, 65-80.
19. Morris, C. N. (1983), "Natural Exponential Families With Quadratic Variance Functions: Statistical Theory, " The Annals of Statistics, 2, 515-529.
20. Sposto, R., Sather, H. N., and Baker, S. A. (1992), "A Comparison of Tests of the Difference in the Proportion of Patients Who are Cured, " Biometrics, 48, 87-99.
21. Stangl, D. K., and Greenhouse, J. B. (1998), "Assessing Placebo Response Using Bayesian Hierarchical Survival Models, " Lifetime Data Analysis, 4, 5-28.
22. Taylor, J. M. G. (1995), "Semi-Parametric Estimation in Failure Time Mixture Models, " Biometrics, 51, 899-907.
23. Yakovlev, A. Y., Asselain, B., Bardou, V. J., Fourquet, A., Hoang, T., Rochefediere, A., and Tsodikov, A. D. (1993), "A Simple Stochastic Model of Tumor Recurrence and Its Applications to Data on Premenopausal Breast Cancer, " in Biometrie et Analyse de Donnees SpatioTemporelles, 12, eds. B. Asselain, M. Boniface, C. Duby, C. Lopez, J. P. Masson, and J. Tranchefort, France, Rennes: Societe Francaise de Biometric, ENSA, 66-82.
24. Yamaguchi, K. (1992), "Accelerated Failure-Time Regression Models With a Regression Model of Surviving Fraction: An Application to the Analysis of 'Permanent Employment' in Japan, " Journal of the American Statistical Association, 87, 284-292.