Dependent Hazards in Multivariate Survival Problems

Journal of Multivariate Analysis

Volumn 71, Issue 2, 1999, Pages 241-261

  Yashin, Anatoli I ^a   Iachine, Ivan A ^b  

^a MAX PLANCK INSTITUTE FOR DEMOGRAPHIC RESEARCH   (Germany)

^b UNIVERSITY OF SOUTHERN DENMARK   (Denmark)

Author keywords

Correlated hazards; bivariate frailty, bivariate survival, mortality models

Indexed keywords

EID: 0141715180     PISSN: 0047259X     EISSN: None     Source Type: Journal    
DOI: 10.1006/jmva.1999.1848     Document Type: Article

References (41)

1. Aalen O. O. Heterogeneity in survival analysis. Statist. Med. 7:1988;1121-1137.
2. Andersen P. K., Borgan O., Gill R. D., Keiding N. Statistical Models Based on Counting Processes. 1992;Springer-Verlag, New York/Berlin.
3. Azzalini A. Statistical Inference Based on the Likelihood. Monographs on Statistics and Applied Probability. 68:1996;Chapman & Hall, London/New York.
4. Clayton D. G. A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika. 65:1978;141-151.
5. Clayton D. G., Cuzick J. Multivariate generalizations of the proportional hazards model (with discussion). J. Roy. Statist. Soc. Ser. A. 148:1985;82-117.
6. Cook R. D., Johnson M. E. A family of distributions for modeling non-elliptically symmetric multivariate data. J. Roy. Statist. Soc. Ser. B. 43:1981;210-218.
7. Cox D. R., Oakes D. Analysis of Survival Data. 1984;Chapman & Hall, New York.
8. Dabrowska D. Kaplan-Meier estimate on the plane. Ann. Statist. 16:1988;1475-1489.
9. David H. A., Moeshberger M. L. The Theory of Competing Risks. 1978;Griffin, High Wycombe.
10. Gavrilov L. A., Gavrilova N. S. The Biology of Life Span: A Quantitative Approach. 1991;Harwood Academic, London/New York.
11. Cederlöf R., Lorich U. The swedish twin registry. Nance W. E. Twin Research: Biology and Epidemiology. 1978;189-195 A. R. Liss, New York.
12. Guo G. Use of sibling data to estimate family mortality effects in Guatemala. Demography. 30:1993;15-32.
13. Guo G., Rodríguez G. Estimating a multivariate proportional hazards model for clustered data using EM algorithm, with an application to child survival in Guatemala. J. Amer. Statist. Assoc. 87:1992;969-976.
14. Heckman J., Singer B. The identifiability of the proportional hazard model. Rev. Econ. Stud. 51:1984;231-241.
15. Hoem J. M. Identifiability in hazard models with unobserved heterogeneity: The compatibility of two apparently contradictory results. Theoret. Population Biol. 37:1990;124-128.
16. P. Hougaard, A class multivariate failure time distributions, 73, No. 1986, 671-678.
17. Hougaard P. Modelling multivariate survival. Scand. J. Statist. 14:1987;291-304.
18. Holt J. D., Prentice R. L. Survival analysis in twin studies and matched pairs experiments. Biometrika. 61:1974;17-30.
19. Iachine I. A. Working Paper Series. 1995.
20. Kalbfleisch J., Prentice R. L. The Statistical Analysis of Failure Time Data. 1980;Wiley, New York.
21. Kaprio J., Sarna S., Koskenvuo M., Rantasalo I. The Finnish twin registry: Formation and compilation, questionnaire study, zygosity determination procedures and research program. Prog. Clin. Biol. Res. B. 24:1978;179-184.
22. Manton K. G., Stallard E., Vaupel J. W. Methods for comparing the mortality experience of heterogeneous populations. Demography. 18:1981;389-410.
23. Marshall A. W., Olkin I. Families of multivariate distributions. J. Amer. Statist. Assoc. 83:1988;834-841.
24. Meyer J. M., Eaves L. J. Estimating genetic parameters of survival distributions: A multifactorial model. Genetic Epidemiol. 5:1988;265-275.
25. Meyer J. M., Eaves L. J., Heath A. C., Martin N. G. Estimating genetic influences on the age at menarche: A survival analysis approach. Amer. Med. Genetics. 39:1991;148-154.
26. Miller R. G. Survival Analysis. 1981;Wiley, New York.
27. Nielsen G. G., Gill R. D., Andersen P. K., Sørensen T. I. A. A counting process approach to maximum likelihood estimation in frailty models. Scand. J. Statist. 19:1992;25-43.
28. Oakes D. Bivariate survival models induced by frailties. J. Amer. Statist. Assoc. 84:1989;487-493.
29. Petersen J. H., Andersen P. K., Gill R. D. Variance components models for survival data. Statist. Neerlandica. 50:1996;193-211.
30. Schweizer B., Sklar A. Probabilistic Metric Spaces. 1983;Elsevier, New York.
31. Thomas D. C., Langholz B., Mack W., Floderus B. Bivariate survival models for analysis of genetic and environmental effects in twins. Genetic Epidemiol. 7:1990;121-135.
32. Vaupel J. W., Manton K. G., Stallard E. The impact of heterogeneity in individual frailty on the dynamics of mortality. Demography. 16:1979;439-454.
33. Vaupel J. W., Yashin A. I. Heterogeneity's ruses: Some surprising effects of selection on population dynamics. Amer. Statist. 39:1985;176-185.
34. Vaupel J. W., Yashin A. I., Hauge M., Harvald B., Holm N., Xue Liang. Survival analysis in genetics: Danish twins data applied to gerontological question. Klein J. P., Goel P. K. Survival Analysis: State of the Art. 1992;Kluwer Academic, Dordrecht.
35. Yashin A. I., Iachine I. A. Mortality models with application to twin survival data (1994). Halin J., Karplus W., Rimane R. Proceedings, CISS, First Joint Conference of International Simulation Societies, Aug. 22-25, 1994. 1994;567-571 ETH, Zurich.
36. Yashin A. I., Vaupel J. W., Iachine I. A. Correlated individual frailty: An advantageous approach to survival analysis of bivariate data. Math. Pop. Stud. 5:1995;145-159.
37. Yashin A. I., Iachine I. A. How long can humans live? Lower bound for biological limit of human longevity calculated from Danish twin data using correlated frailty model. Mech. Ageing Develop. 80:1995a;147-169.
38. Yashin A. I., Iachine I. A. Genetic analysis of durations: Correlated frailty model applied to survival of Danish twins. Genetic Epidemiol. 12:1995b;529-538.
39. Yashin A. I., Iachine I. A. Survival of related individuals: An extension of some fundamental results of heterogeneity analysis. Math. Pop. Stud. 5:1995c;321-329.
40. Yashin A. I., Iachine I. A. Surprising Dynamics of Hazards in the Dependent Competing Risks Problem: The Case of Correlated Frailty. Population Studies of Aging. 1996;Odense University, Denmark.
41. Yashin A. I., Iachine I. A. How frailty models can be used in the analysis of mortality and longevity limits. Demography. 34:1997;31-48.