Semiparametric regression analysis of mean residual life with censored survival data

Biometrika

Volumn 92, Issue 1, 2005, Pages 19-29

  Chen, Y Q ^a   Cheng, S ^b  

^a Fred Hutchinson Cancer Research Center   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Counting process; Estimating equation; Failure time; Life expectancy; Proportional model; Stochastic process

Indexed keywords

EID: 15844427066     PISSN: 00063444     EISSN: None     Source Type: Journal    
DOI: 10.1093/biomet/92.1.19     Document Type: Article

References (14)

1. CHENG, S. C., WEI, L. J. & YING, Z. (1995). Analysis of transformation models with censored data. Biometrika 82, 835-45.
2. COX, D. R. (1962). Renewal Theory. New York: Wiley.
3. COX, D. R. (1972). Regression models and life-tables (with Discussion). J. R. Statist. Soc. B 34, 187-220.
4. FLEMING, T. R. & HARRINGTON, D. P. (1991). Counting Process and Survival Analysis. New York: Wiley.
5. HALL, W. J. & WELLNER, J. A. (1981). Mean residual life. In Proc. Int. Symp. Statist, and Related Topics, Ed. M. Csörgö, D. A. Dawson, J. N. K. Rao and A. K. Md. E. Saleh, pp. 169-81. Amsterdam: North-Holland.
6. LAI, T. L. & YING, Z. (1992). Asymptotically efficient estimation in censored and truncated regression models. Statist. Sinica 2, 17-46.
7. MAGULURI, G. & ZHANG, C.-H. (1994). Estimation in the mean residual life regression model. J. R. Statist. Soc. B 56, 477-89.
8. OAKES, D. & DASU, T. (1990). A note on residual life. Biometrika 77, 409-10.
9. OAKES, D. & DASU, T. (2003). Inference for the proportional mean residual life model. In Crossing Boundaries: Statistical Essays in Honor of Jack Hall, Institute of Mathematical Statistics Lecture Notes Monograph Series, Vol. 43, Ed. J. E. Kolassa and D. Oakes, pp. 105-16. Hayward, CA: Institute of Mathematical Statistics.
10. PETTITT, A. N. (1984). Proportional odds model for survival data and estimates using ranks. Appl. Statist. 33, 169-75.
11. PRENTICE, R. L. (1973). Exponential survivals with censoring and explanatory variables. Biometrika 60, 279-88.
12. ROBINS, J. M. & ROTNITZKY, A. (1992). Recovery of information and adjustment for dependent censoring using surrogate markers. In AIDS Epidemiology, Methodological Issues, Ed. N. P. Jewell, K. Dietz and V. Farewell, pp. 297-331. Boston: Birkhäuser.
13. SERFLING, R. J. (1980). Approximation Theorems of Mathematical Statistics. New York: Wiley.
14. YING, Z. (1993). A large sample study of rank estimation for censored regression data. Ann. Statist. 21, 76-99.