Analysis of survival data with multiple causes of failure: A comparison of hazard- and logistic-regression models with application in demography

Quality and Quantity

Volumn 32, Issue 3, 1998, Pages 297-324

  Ghilagaber, Gebrenegus ^a  

^a UPPSALA UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; FAMILY AND HOUSEHOLD; FAMILY SIZE; MARRIAGE; MARRIAGE PATTERNS; METHODOLOGY; NUPTIALITY; RESEARCH; THEORETICAL MODEL; WORLD;

FAMILY AND HOUSEHOLD; FAMILY CHARACTERISTICS; MARRIAGE; MARRIAGE PATTERNS; MODELS, THEORETICAL; NUPTIALITY; RESEARCH METHODOLOGY; WORLD;

FAMILY CHARACTERISTICS; MARRIAGE; MODELS, THEORETICAL; RESEARCH;

EID: 0032129861     PISSN: 00335177     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1004312403022     Document Type: Article

References (47)

1. Allison, P. D. (1984). Event History Analysis: Regression for Longitudinal Event Data. Sage University Paper series on Quantitative Applications in the Social Sciences, 07-046. Beverly Hills and London: Sage Publications.
2. Breslow, N. E. & Day, N. E. (1975). Indirect standardization and multiplicative models for rates, with reference to the age adjustment of cancer incidence and relative frequency data. Journal of Chronic Diseases 28: 289-303.
3. Buckley, J. D. (1984). Additive and multiplicative models for relative survival rates. Biometrics 40: 51-62.
4. Carling, K. & Jacobson, T. (1995). Modeling unemployment duration in a dependent competing risks framework: Identification and estimation. Lifetime Data Analysis 1: 111-122.
5. Cox, D. R. (1972). Regression models and life-tables (with discussion). Journal of the Royal Statistical Society - Series B 34: 187-220.
6. Cox, D. R. (1975). Partial likelihood. Biometrika 62: 269-276.
7. David, H. A. & Moeschberger, M. L. (1978). The Theory of Competing Risks. Griffin's Statistical Monographs No. 39. New York: MacMillan.
8. Elandt-Johnson, R. C. & N. L. Johnson (1980). Survival Models and Data Analysis. New York: Wiley.
9. Ghilagaber, G. (1993a). Family initiation among Swedish males born 1936-1964: The choice between marriage and cohabitation. Stockholm Research Reports in Demography 77: Demography Unit, Stockholm University.
10. Ghilagaber, G. (1993b). The relationship between premarital cohabitation and marital stability: Evidence for Swedish men born between 1936 and 1960. Stockholm Research Reports in Demography 80: Demography Unit, Stockholm University.
11. Ghilagaber, G. (1995a). Similarities among some hazard-rate and duration models for grouped and continuous lifetime data with covariates: An exploration and application to modeling correlates of marital dissolution. Research Report 95-3: Department of Statistics, Uppsala University.
12. Ghilagaber, G. (1995b). A competing-risks analysis of the choice between marriage and cohabitation: Experience of Swedish men born in 1936-1964. In: C. Lundh (ed.), Demography, Economy and Welfare. Lund University Press, pp. 64-76.
13. Ghilagaber, G. (1996). Simultaneous log-linear modeling of multiple risks: A demographic illustration on the need to distinguish among various hazards. Paper presented at the 16th Nordic Conference in Mathematical Statistics. Lahti - Finland, 18-22 August 1996.
14. Gomez-De Leon, J. & Potter, J. E. (1989). Modeling the inverse association between breastfeeding and contraceptive use. Population Studies 43: 69-93.
15. Hachen, D. S. (1988). The competing risks model: A method for analysing processes with multiple types of events. Sociological Methods and Research 17: 21-54.
16. Han, A. & Hausman, J. A. (1990). Flexible parametric estimation of duration and competing risks models. Journal of Applied Econometrics 5: 1-28.
17. Hoem, J. M. (1985). Logistisk regression med LOGLIN (Logistic regression with LOGLIN). Intern Prememoria 85-07-25: Demography Unit, Stockholm University.
18. Hoem, J. M. (1987). Statistical analysis of a multiplicative model and its application to the standardisation of vital rates. International Statistical Review 55: 119-152.
19. Holford, T. R. (1980). The analysis of rates and survivorship using log-linear models. Biometrics 36: 299-305.
20. Hosmer, D. W. & Lemeshow, S. (1989). Applied Logistic Regression. New York: Wiley.
21. Johansson, L. (1991). Män och barn: Svenska mäns familjebildning och barnplanner (Men and children: Swedish men's family formation and child plans). Demografiska rapporter 1990(2), Statistics Sweden, Örebro.
22. Kaplan, E. L. & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 53: 457-481.
23. Klein, J. P. & Moeschberger, M. L. (1984). Asymptotic bias of the product limit estimator under dependent competing risks. Journal of the Indian Association for Productivity, Quality, and Reliability 9: 1-7.
24. Klein, J. P. & Moeschberger, M. L. (1987). Independent or dependent competing risks: Does it make a difference. Communications in Statistics-Simulation and Computation 16: 507-533.
25. Kotz, S. & Johnson, N. L. (eds) (1982). Encyclopedia of Statistical Sciences Vol. 2.
26. Lagakos, S. W. (1979). General right censoring and its impact on the analysis of survival data. Biometrics 35: 139-156.
27. Laird, N. & Olivier, D. (1981). Covariance analysis of censored survival data using log-linear analysis techniques. Journal of the American Statistical Association 76: 231-240.
28. Larson, M. G. (1984). Covariate analysis of competing-risks data with log-linear models. Biometrics 40: 459-469.
29. Liefbroer, A. C. (1991). The choice between married and unmarried first union by young adults: A competing risk analysis. European Journal of Population 7: 273-298.
30. Lindsey, J. K. (1975). A comparision of additive and multiplicative models for qualitative data. Quality and Quantity 9: 43-50.
31. Lindsey, J. K. (1995). Fitting parametric counting processes by using log-linear models. Applied Statistics 44: 201-212.
32. Martinelle, S. (1993). RocaNova: A program for Intensity Regression-Version 1.0. Statistics Sweden, Stockholm.
33. Narendranathan, W. & Stewart, M. B. (1991). Simple methods for testing for the proportionality of cause-specific hazards in competing risks models. Oxford Bulletin of Economics and Statistics 53: 331-340.
34. Narendranathan, W. & Stewart, M. B. (1993). Modelling the probability of leaving unemployment: Competing risks models with flexible baseline hazards. Applied Statistics 42: 63-83.
35. Nour, E.-S. E. (1981). Multiple decrement analysis with dependent risks. Biometrical Journal 23: 175-183.
36. Olivier, D. C. & Neff, R. K. (1976). LOGLIN 1.0 User's Guide. Harvard University.
37. Osborn, J. (1975). A multiplicative model for the analysis of vital statistical rates. Applied Statistics 24: 75-84.
38. Prentice, R. L., Kalbfleisch, J. D., Peterson, Jr, A. V., Flourney, N., Farewell, V. T. & Breslow, N. E. (1978). The analysis of failure times in the presence of competing risks. Biometrics 34: 541-554.
39. Robertson, J. B. & Uppuluri, V. R. R. (1984). A generalized Kaplan-Meier estimator. The Annals of Statistics 12: 366-371.
40. SAS Institute, Inc. (1991). SAS/STAT users guide for personal computers - Version 6.04. Cary, NC.
41. Slud, E. V. & Rubinstein, L. V. (1983). Dependent competing risks and summary survival curves. Biometrika 70: 643-649.
42. Slud, E. & Byar, D. (1988). How dependent causes of death can make risk factors appear protective. Biometrics 44: 265-269.
43. Sörensen, A. (1983). Women's employment patterns after marriage. Journal of Marriage and the Family 45: 311-321.
44. Teachman, J. D. (1983). Analyzing social processes: Life tables and proportional hazards models. Social Science Research 12: 263-301.
45. Tibshirani, R. J. & Ciampi, A. (1983). A family of proportional and additive-hazards models for survival data. Biometrics 39: 141-147.
46. Walter, S. D. & Holford, T. R. (1978). Additive, multiplicative, and other models for disease risks. American Journal of Epidemiology 108: 341-346.
47. Yashin, A. I., Manton, K. G. & Stallard, E. (1986). Dependent competing risks: A stochastic process model. Journal of Mathematical Biology 24: 119-140.