Semiparametric left truncation and right censorship models with missing censoring indicators

Statistics and Probability Letters

Volumn 78, Issue 16, 2008, Pages 2572-2577

  Subramanian, Sundarraman ^a   Bandyopadhyay, Dipankar ^b  

^a NEW JERSEY INSTITUTE OF TECHNOLOGY   (United States)

^b MEDICAL UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 53249119006     PISSN: 01677152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.spl.2008.07.021     Document Type: Article

References (20)

1. Andersen P.K., Borgan O., Gill R.D., and Keiding N. Statistical Models Based on Counting Processes (1993), Springer-Verlag, New York
2. Arcones M.A., and Giné E. On the law of the iterated logarithm for canonical U-statistics and processes. Stochastic Process. Appl. 58 (1995) 217-245
3. Dikta G. On semiparametric random censorship models. J. Statist. Plann. Inference 66 (1998) 253-279
4. Dikta G., Ghorai J., and Schmidt C. The central limit theorem under semiparametric random censorship models. J. Statist. Plann. Inference 127 (2005) 23-51
5. Gijbels I., and Wang J.L. Strong representations of the survival function estimator for truncated and censored data with applications. J. Multivariate Anal. 47 (1993) 210-229
6. Gu M.G., and Lai T.L. Functional laws of the iterated logarithm for the product-limit estimator of a distribution function under random censorship or truncation. Ann. Probab. 18 (1990) 160-189
7. Koul H., Susarla V., and Van Ryzin J. Regression analysis with randomly right censored data. Ann. Statist. 9 (1981) 1276-1288
8. Little R.J.A., and Rubin D.B. Statistical Analysis with Missing Data (1987), Wiley, New York
9. Rao C.R. Linear Statistical Inference and its Applications. 2nd ed. (1973), Wiley, New York
10. Robins J.M., and Rotnitzky A. Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell N., Dietz K., and Farewell V. (Eds). AIDS Epidemiology Methodological Issues (1992), Birkhauser, Boston 297-331
11. Satten G.A., and Datta S. The Kaplan-Meier estimator as an inverse-probability-of-censoring weighted average. Amer. Statist. 55 (2001) 207-210
12. Subramanian S. The missing censoring-indicator model of random censorship. In: Balakrishnan N., and Rao. C.R. (Eds). Handbook of Statistics 23: Advances in Survival Analysis (2004) 123-141
13. Subramanian S. Survival analysis for the missing censoring indicator model using kernel density estimation techniques. Stat. Methodol. 3 (2006) 125-136
14. Subramanian, S., Bean, D., 2008. Hazard function estimation from homogeneous right censored data with missing censoring indicators. Stat. Methodol. 5. (in press)
15. Subramanian, S., Bandyopadhyay, D., 2008. Semiparametric models for left truncation and right censoring with missing censoring indicators. CAMS Technical Report, Department of Mathematical Sciences, New Jersey Institute of Technology
16. Sun L. The strong law under a semiparametric model for truncated and censored data. Statist. Probab. Lett. 76 (2006) 1550-1558
17. Sun L., and Zhu L. A semiparametric model for truncated and censored data. Statist. Probab. Lett. 48 (2000) 217-227
18. Wang M.C. A semiparametric model for randomly truncated data. J. Amer. Statist. Assoc. 84 (1989) 742-748
19. Wang M.C., Jewell N.P., and Tsai W.Y. Asymptotic properties of the product limit estimate under random truncation. Ann. Statist. 14 (1987) 1597-1605
20. Woodroofe M. Estimating a distribution function with truncated data. Ann. Statist. 13 (1985) 163-177 1987. 15, 883 (Correction)