Semiparametric Analysis of Recurrent Events Data in the Presence of Dependent Censoring

Biometrics

Volumn 59, Issue 4, 2003, Pages 877-885

  Ghosh, Debashis ^a   Lin, D Y ^b  

^a UNIVERSITY OF MICHIGAN SCHOOL OF PUBLIC HEALTH   (United States)

^b IL   (United States)

Author keywords

Accelerated failure time model; Competing risks; Counting process; Empirical process; Multiple events; Survival analysis

Indexed keywords

NUMERICAL METHODS; RISK ASSESSMENT; SAMPLING;

ACCELERATED FAILURE TIME MODEL; COMPETING RISKS; COUNTING PROCESS; EMPIRICAL PROCESS; FAILURE TIME; MULTIPLE EVENTS; RECURRENT EVENTS; SEMIPARAMETRIC; SURVIVAL ANALYSIS; TIME MODELING;

REGRESSION ANALYSIS;

MODEL;

ACQUIRED IMMUNE DEFICIENCY SYNDROME; ARTICLE; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; INTRAVENOUS DRUG ABUSE; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; PROBABILITY; REGRESSION ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICAL PARAMETERS;

HUMAN IMMUNODEFICIENCY VIRUS;

EID: 0346733306     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2003.00102.x     Document Type: Article

References (29)

1. Albert, P. S. (1991). A two-state Markov mixture model for a time series of epileptic seizure counts. Biometrics 47, 1371-1381.
2. Andersen, P. K. and Gill, R. D. (1982). Cox's regression model for counting processes: A large sample study. Annals of Statistics 10, 1100-1120.
3. Byar, D. P. (1980). The Veterans Administration study of chemoprophylaxis for recurrent stage I bladder tumors: Comparisons of placebo, pyridoxine and topical thiotepa. In Bladder Tumors and Other Topics in Urological Oncology, M. Pavone-Macaluso, P. H. Smith, and F. Edsmyr (eds), 363-370. New York: Plenum.
4. Chang, S.-H. (2000). A two-sample comparison for multiple ordered event data. Biometrics 56, 183-189.
5. Cox, D. R. and Oakes, D. (1984). Analysis of Survival Data. London: Chapman and Hall.
6. Fleming, T. R. and Harrington, D. P. (1991). Counting Processes and Survival Analysis. New York: Wiley.
7. Ghosh, D. (2000). Nonparametric and semiparametric analysis of recurrent events in the presence of terminal events and dependent censoring. Ph.D. thesis, University of Washington.
8. Ghosh, D. and Lin, D. Y. (2000). Nonparametric analysis of recurrent events and death. Biometrics 56, 554-562.
9. Ghosh, D. and Lin, D. Y. (2002). Marginal regression models for recurrent and terminal events. Statistica Sinica 12, 663-688.
10. Kalbfleisch, J. D. and Prentice, R. L. (1980). The Statistical Analysis of Failure Time Data. New York: Wiley.
11. Lawless, J. F. and Zhan, M. (1998). Analysis of interval-grouped recurrent-event data using piecewise constant rate functions. Canadian Journal of Statistics 26, 549-565.
12. Lawless, J. F., Nadeau, C., and Cook, R. J. (1997). Analysis of mean and rate functions for recurrent events. In Proceedings of the First Seattle Survival Analysis Symposium, D. Y. Lin and T. R. Fleming (eds), 137-149. New York: Springer.
13. Lee, J. J., Li, K.-C., and Elashoff, R. M. (1993). On recensoring for censored paired data. Journal of the American Statistical Association 88, 104-118.
14. Li, Q. and Lagakos, S. (1997). Use of the Wei-Lin-Weissfeld method for the analysis of a recurring and a terminating event. Statistics in Medicine 16, 925-940.
15. Lin, D. Y., Robins, J. M., and Wei, L. J. (1996). Comparing two failure time distributions in the presence of dependent censoring. Biometrika 83, 381-393.
16. Lin, D. Y., Wei, L. J., and Ying, Z. (1998). Accelerated failure time models for counting processes. Biometrika 85, 605-618.
17. Parzen, M. I., Wei, L. J., and Ying, Z. (1994). A resampling method based on pivotal estimating functions. Biometrika 81, 341-350.
18. Pepe, M. S. and Cai, J. (1993). Some graphical displays and marginal regression analyses for recurrent failure times and time dependent covariates. Journal of the American Statistical Association 88, 811-820.
19. Prentice, R. L., Williams, B. J., and Peterson, A. V. (1981). On the regression analysis of multivariate failure time data. Biometrika 68, 373-379.
20. Ramsay, J. O. (1988). Monotone regression splines in action (with discussion). Statistical Science 3, 425-461.
21. Robins, J. and Rotnitzky, A. (1992). Recovery of information and adjustment for dependent censoring using surrogate markers. In Aids Epidemiology-Methodological Issues, N. Jewell, K. Dietz, and V. Farewell (eds), 297-331. Boston: Birkhäuser.
22. Scharfstein, D. O., Rotnitzky, A., and Robins, J. M. (1999). Adjusting for nonignorable drop-out using semiparametric nonresponse models (with comments and rejoinder). Journal of the American Statistical Association 94, 1096-1146.
23. Sun, J. and Wei, L. J. (2000). Regression analysis of panel count data with covariate-dependent observation and censoring times. Journal of the Royal Statistical Society, Series B 62, 293-302.
24. Tsiatis, A. A. (1990). Estimating regression parameters using linear rank tests for censored data. Annals of Statistics 18, 354-372.
25. Vlahov, D., Anthony, J. C., Muñoz, A., Margolick, J., Nelson, K. E., Celentano, D. D., Solomon, L., and Polk, B. F. (1991). The ALIVE study: A longitudinal study of HIV-1 infection in intravenous drug users: Description of methods. Journal of Drug Issues 21, 759-776.
26. Wang, M. C., Qin, J., and Chiang, C. T. (2001). Analyzing recurrent event data with informative censoring. Journal of the American Statistical Association 96, 1057-1065.
27. Wei, L. J. (1984). Testing goodness of fit for proportional hazards model with censored observations. Journal of the American Statistical Association 79, 649-652.
28. Wei, L. J., Lin, D. Y., and Weissfeld, L. (1989). Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. Journal of the American Statistical Association 84, 1065-1073.
29. Ying, Z. (1993). A large sample study of rank estimation for censored regression data. Annals of Statistics 21, 76-99.