Statistical methods for analyzing right-censored length-biased data under cox model

Biometrics

Volumn 66, Issue 2, 2010, Pages 382-392

  Qin, Jing ^a   Shen, Yu ^b  

^a NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES   (United States)

^b UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

Author keywords

Cox model; Dependent censoring; Estimating equation; Length biased

Indexed keywords

COMPUTATION THEORY; POPULATION STATISTICS; RISK ASSESSMENT; STOCHASTIC SYSTEMS;

CANCER PREVENTION; COHORT STUDIES; COVARIATES; COX MODEL; DEPENDENT CENSORING; ESTIMATING EQUATIONS; LENGTH BIASED; LENGTH-BIASED DATA; STATISTICAL PROBLEMS; TIME TO EVENTS;

RANDOM PROCESSES;

ALGORITHM; CANCER; EPIDEMIOLOGY; ERROR ANALYSIS; HAZARD ASSESSMENT; LENGTH-FREQUENCY ANALYSIS; RISK FACTOR; SAMPLING; SIMULATION;

ALGORITHM; HUMAN; POPULATION AND POPULATION RELATED PHENOMENA; PROPORTIONAL HAZARDS MODEL; RISK FACTOR; STATISTICAL MODEL; SURVIVAL;

ALGORITHMS; EPIDEMIOLOGIC MEASUREMENTS; HUMANS; MODELS, STATISTICAL; PROPORTIONAL HAZARDS MODELS; RISK FACTORS; SURVIVAL ANALYSIS;

EID: 77952996245     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2009.01287.x     Document Type: Article

References (25)

1. Andersen, P. K., Borgan, O., Gill, R. D., and Keiding, N. (1993). Statistical Models Based on Counting Processes.
2. Asgharian, M. and Wolfson, D. B. (2005). Asymptotic behavior of the unconditional NPMLE of the length-biased survivor function from right censored prevalent cohort data. Annals of Statistics 33, 2109 2131.
3. Asgharian, M., M'Lan, C. E., and Wolfson D. B. (2002). Length-biased sampling with right censoring: An unconditional approach. Journal of the American Statistical Association 97, 201 209.
4. Asgharian, M., Wolfson, D. B., and Zhang, X. (2006). Checking stationarity of the incidence rate using prevalent cohort survival data. Statistics in Medicine 25, 1751 1767.
5. Bergeron, P.-J., Asgharian, M., and Wolfson, D. B. (2008). Covariate bias induced by length-biased sampling of failure times. Journal of the American Statistical Association 103, 737 742.
6. Cox, D. R. (1972). Regression models and life-tables (with discussion). Journal of the Royal Statistical Society, Series B 34, 187 220.
7. de Una-Alvarez, J. Otero-Giraldez, M. S., and Alvarez-Llorente, G. (2003). Estimation under length-bias and right-censoring: An application to unemployment duration analysis for married women. Journal of Applied Statistics 30, 283 291.
8. Ghosh, D. (2008). Proportional hazards regression for cancer studies. Biometrics 64, 141 148.
9. Gill, R. D., Vardi, Y., and Wellner, J. A. (1988). Large-sample theory of empirical distributions in biased sampling models. Annals of Statistics 16, 1069 1112.
10. Kalbfleisch, J. D. and Lawless, J. F. (1991). Regression models for right truncated data with applications to AIDS incubation times and reporting lags. Statistica Sinica 1, 19 32.
11. Keiding, N. (1992). Independent delayed entry. In Survival Analysis: State of the Art, J. P. Klein and P. K. Goel (eds 309 325.
12. Lagakos, S. W., Barraj, L. M., and De Gruttola, V. (1988). Nonparametric analysis of truncated survival data, with applications to AIDS. Biometrika 75, 515 523.
13. Lancaster, T. (1979). Econometric methods for the duration of unemployment. Econometrica 47, 939 956.
14. Pepe, M. S. and Fleming, T. R. (1991). Weighted Kaplan-Meier statistics: Large sample and optimality considerations. Journal of the Royal Statistical Society, Series B 53, 341 352.
15. Shen, Y., Ning, J., and Qin, J. (2009). Analyzing length-biased data with semiparametric transformation and accelerated failure time models Journal of the American Statistical Association.
16. Turnbull, B. W. (1976). The empirical distribution function with arbitrarily grouped, censored and truncated data. Journal of the Royal Statistical Society, Series B 38, 290 295.
17. Vardi, Y. (1982). Nonparametric estimation in the presence of length bias. Annals of Statistics 10, 616 620.
18. Vardi, Y. (1985). Empirical distributions in selection bias models. Annals of Statistics 13, 178 203.
19. Vardi, Y. (1989). Multiplicative censoring, renewal processes, deconvolution and decreasing density: Nonparametric estimation. Biometrika 76, 751 761.
20. Wang, M. C. (1989). A semiparametric model for randomly truncated data. Journal of the American Statistical Association 84, 742 748.
21. Wang, M. C. (1996). Hazards regression analysis for length-biased data. Biometrika 83, 343 354.
22. Wang, M. C., Brookmeyer, R., and Jewell, N. P. (1993). Statistical models for prevalent cohort data. Biometrics 49, 1 11.
23. Wolfson, C., Wolfson, D. B., Asgharian, M., M'Lan, C. E., Ostbye, T., Rockwood, K., and Hogan, D. B. for the Clinical Progression of Dementia Study Group (2001). A reevaluation of the duration of survival after the onset of dementia. New England Journal of Medicine 344, 1111 1116.
24. Zelen, M. (2004). Forward and backward recurrence times and length biased sampling: Age specific models. Lifetime Data Analysis 10, 325 334.
25. Zelen, M. and Feinleib M. (1969). On the theory of screening for chronic diseases. Biometrika 56, 601 614.