Two-stage estimation in copula models used in family studies

Lifetime Data Analysis

Volumn 11, Issue 3, 2005, Pages 333-350

  Andersen, Elisabeth Wreford ^a,b,c  

^a DEPARTMENT OF EPIDEMIOLOGY RESEARCH   (Denmark)

^b UNIVERSITY OF COPENHAGEN   (Denmark)

^c H LUNDBECK A S   (Denmark)

Author keywords

Copula models; Register based family studies; Sampled cohorts; Two stage estimation

Indexed keywords

ARTICLE; COHORT ANALYSIS; FAMILY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

COHORT STUDIES; DATA INTERPRETATION, STATISTICAL; FAMILY; MODELS, STATISTICAL;

EID: 24144477937     PISSN: 13807870     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10985-005-2966-7     Document Type: Article

References (19)

1. D. A. Binder, "Fitting Cox's proportional hazards models from survey data," Biometrika vol. 79 pp. 139-147, 1992.
2. D. R. Cox and D.V. Hinkley, Theoretical Statistics, Chapman and Hall: New York, 1974.
3. C. Genest and J.MacKay, "The joy of copulas," The American Statistician vol. 40 pp. 280-283, 1986.
4. D. V. Glidden, "Checking the adequacy of the gamma frailty model for multivariate failure times," Biometrika vol. 86 pp. 381-393, 1999.
5. D. V. Glidden, "A two-stage estimator of the dependence parameter for the Clayton-Oakes model," Lifetime Data Analysis vol. 6 pp. 141-156, 2000.
6. P. Hougaard, "A class of multivariate failure time distributions," Biometrika vol. 73 pp. 671-678, 1987.
7. P. Hougaard, Analysis of Multivariate Survival Data, Statistics for Biology and Health: Springer-Verlag, 2000.
8. P. Hougaard, B. Harvald and N. Holm, "Measuring the similarities between the lifetimes of adult Danish twins born between 1881-1930," Journal of the American Statistical Association vol. 87 pp. 17-24, 1992.
9. E. W. Lee, L. J. Wei, and D. A. Amato, "Cox-type regression analysis for large numbers of small groups of correlated failure time observations," in Survival Analysis: State of the Art, (J. Klein and P. Goel, eds.) Kluwer and Dordrecht, pp. 237-247, 1992.
10. D. Y. Lin, "Cox regression analysis of multivariate failure time data: The marginal approach," Statistics in Medicine vol. 13 pp. 2233-2247, 1994.
11. D. Y. Lin, "On fitting Cox's proportional hazards models to survey data," Biometrika vol. 87 pp. 37-47, 2000.
12. G. G. Nielsen, R. D. Gill, P. K. Andersen and T. I. A. Sørensen, "A counting process approach to maximum likelihood estimation in frailty models," Scandinavian journal of Statistics vol. 19 pp. 25-43, 1992.
13. D. Oakes, "Bivariate survival models induced by frailties," Journal of the American Statistical Association vol. 84 pp. 487-493, 1989.
14. S. G. Self and K.-Y. Liang, "Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard conditions," Journal of the American Statistical Association vol. 82 pp. 605-610, 1987.
15. J. H. Shih and T. A. Louis, "Assessing gamma frailty models for clustered failure time data," Lifetime Data Analysis vol. 1 pp. 205-220, 1995a.
16. J. H. Shih and T. A. Louis, "Inferences on association parameter in copula models for bivariate survival data," Biometrics vol. 51 pp. 1384-1399, 1995b.
17. C. F. Spiekerman and D. Y. Lin, "Checking the marginal Cox model for correlated failure time data," Biometrika vol. 83 pp. 143-156, 1996.
18. C. F. Spiekerman and D. Y. Lin, "Marginal regression models for multivariate failure time data," Journal of the American Statistical Association vol. 93 pp. 1164-1175, 1998.
19. L. J. Wei, D. Y. Lin and L. Weissfleld, "Regression analysis of multivariate incomplete failure time data by modeling marginal distributions," Journal of the American Statistical Association vol. 84 pp. 1068-1073, 1989.