Some comments on efficiency gains from auxiliary information for right-censored data

Journal of Statistical Planning and Inference

Volumn 96, Issue 1, 2001, Pages 191-202

  Cook, R J ^a   Lawless, J F ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0042408282     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0378-3758(00)00335-9     Document Type: Article

References (21)

1. Andersen P.K., Borgan O., Gill R.D., Keiding N. Statistical Models Based on Counting Processes. 1993;Springer, New York.
2. Conniffe D. A comment on the use of auxiliary or surrogate outcome data. J. Statist. Planning Inf. 55:1996;353-359.
3. Engel B., Walstra P. Increasing precision or reducing expense in regression by using information from a concomitant variable. Biometrics. 47:1991;13-20.
4. Finkelstein D.M., Schoenfeld D.A. Analyzing survival in the presence of an auxiliary variable. Statist. Med. 13:1994;1747-1754.
5. Flandre P. On the use of auxiliary data to estimate the survival function and its variance: an application to Acquired Immunodeficiency Syndrome. J. Clin. Epidemiol. 49:1996;899-905.
6. Flandre P. Analysing survival in the presence of an auxiliary variable (Letter to the Editor). Statist. Med. 17:1998;239-241.
7. Fleming T.R., Prentice R.L., Pepe M.S., Glidden D. Surrogate and auxiliary endpoints in clinical trials with potential applications in cancer and AIDS research. Statist. Med. 13:1994;955-968.
8. Gray R.J. A kernel method for incorporating information on disease progression in the analysis of survival. Biometrika. 81:1994;527-540.
9. Kosorok M.R., Fleming T.R. Using surrogate failure time data to increase cost effectiveness in clinical trials. Biometrika. 80:1993;823-833.
10. Lagakos S.W. A stochastic model for censored-survival data in the presence of an auxiliary variable. Biometrics. 32:1976;551-559.
11. Lagakos S.W. Using auxiliary variables for improved estimates of survival time. Biometrics. 33:1977;399-404.
12. MacKenzie, T.A., 1997. The use of markers to enhance time-to-event analysis. Unpublished Ph.D. Thesis, Department of Mathematics and Statistics, McGill University Montreal, Canada.
13. Malani H.M. A modification of the re-distribution to the right algorithm using disease markers. Biometrika. 82:1995;515-526.
14. Malani, H.M., Nielsen, J.P., 1990. Use of the two stage model for improving the estimate of the survivor function. Tech. Rep. No. 17, Group in Biostatistics, University of California, Berkeley.
15. Malani H.M., Redfearn W.J., Nielsen J.P. A note on the asymptotic variance of survival function in the semi-Markov model. Statist. Probab. Lett. 18:1993;19-25.
16. Murray S., Tsiatis A.A. Nonparametric survival estimation using prognostic longitudinal covariates. Biometrics. 52:1996;137-151.
17. Pepe M.S. Inference using surrogate outcome data and a validation sample. Biometrika. 79:1992;355-365.
18. Pepe M.S., Reilly M., Fleming T.R. Auxiliary outcome data and the mean score method. J. Statist. Planning Inf. 42:1994;137-160.
19. Robins, J.M., Rotnitzky, A., 1992. Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell, N., Dietz, K., Farewell, V. (Eds.), AIDS Epidemiology: Methodological Issues, Birkhauser-Boston: Boston, pp. 297-331.
20. Slud E., Korn E. Semiparametric two-sample tests in clinical trials with a post-radomization response indicator. Biometrika. 84:1997;221-230.
21. White H. Maximum likelihood estimation of misspecified models. Econometrica. 50:1982;1-25.