Corrected score estimator for joint modeling of longitudinal and failure time data

Statistica Sinica

Volumn 16, Issue 1, 2006, Pages 235-253

  Wang, C Y ^a  

^a Fred Hutchinson Cancer Research Center   (United States)

Author keywords

Empirical process; Estimating equation; Measurement error; Proportional hazards; Random effects

Indexed keywords

EID: 33646416766     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (20)

1. Andersen, P. K. and Gill, R. D. (1982). Cox's regression model for counting processes: a large sample study. Ann. Statist. 10, 1100-1120.
2. Bilias, Y., Gu, M. and Ying, Z. (1997). Towards a general asymptotic theory for Cox model with staggered entry. Ann. Statist. 25, 662-682.
3. Buzas, J. S. (1998). Unbiased scores in proportional hazards regression with covariate measurement error. J. Statist. Plann. Inference 67, 247-257.
4. Carroll, R. J., Ruppert, D. and Stefanski, L. A. (1995). Nonlinear Measurement Error Models. Chapman and Hall. London.
5. Cox, D. R. (1972). Regression models and life tables (with discussion). J. Roy. Statist. Soc. Ser. B 34, 187-220.
6. Dafni, U. G. and Tsiatis, A. A. (1998). Evaluating surrogate markers of clinical outcome measured with error. Biometrics 54, 1445-1462.
7. Hu, C and Lin, D. Y. (2002). Cox regression with covariate measurement error. Scand. J. Statist. 29, 637-655.
8. Huang, Y. and Wang, C. Y. (2000). Cox regression with accurate covariates unascertainable: a nonparametric-correction approach. J. Amer. Statist. Assoc. 95, 1209-1219.
9. Kong, F. H. and Gu, M. (1999). Consistent estimation in Cox proportional hazards model with covariate measurement errors. Statist. Sinica 9, 953-969.
10. Laird, N. M. and Ware, J. H. (1982). Random-effect models for longitudinal data. Biometrics 38, 963-974.
11. Nakamura, T. (1992). Proportional hazards models with covariates subject to measurement error. Biometrics 48, 829-838.
12. Prentice, R. L. (1982). Covariate measurement errors and parameter estimation in a failure time regression model. Biometrika 69, 331-342.
13. Shorack, G. R. and Wellner, J. A. (1986). Empirical processes with applications to statistics. Wiley, New York.
14. Song, X., Davidian, M. and Tsiatis, A. A. (2002). An estimator for the proportional hazards model with multiple longitudinal covariates measured with error. Biostatistics 3, 511-528.
15. Stefanski, L. A. and Carroll, R. J. (1987). Conditional scores and optimal scores for generalized linear measurement-error models. Biometrika 74, 703-716.
16. Tsiatis, A. A. and Davidian, D. (2001). A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error. Biometrika 88, 447-458.
17. Tsiatis, A. A., DeGruttola, V. and Wulfsohn, M. S. (1995). Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 count in patients with AIDS. J. Amer. Statist. Assoc. 90, 27-37.
18. van der Vaart, A. W. and Wellner, J. A. (1996). Weak Convergence and Empirical Processes. Springer-Verlag, New York.
19. Wang, C. Y., Wang, N. and Wang, S (2000). Regression analysis when covariates are regression parameters of a random effect model for observed longitudinal measurements. Biometrics56, 487-495.
20. Xie, S. X., Wang, C. Y. and Prentice, R. L. (2001). A risk set calibration method for failure time regression using a covariate reliability sample. J. Roy. Statist. Soc. Ser. B 63, 855-870.