Estimation of Linear Error-in-Covariables Models with Validation Data Under Random Censorship

Journal of Multivariate Analysis

Volumn 74, Issue 2, 2000, Pages 245-266

  Wang, Qihua ^a,b  

^a PEKING UNIVERSITY   (China)

^b INSTITUTE OF APPLIED MATHEMATICS   (China)

Author keywords

Asymptotic normality; Linear model; Random censoring; Validation data

Indexed keywords

EID: 0348000624     PISSN: 0047259X     EISSN: None     Source Type: Journal    
DOI: 10.1006/jmva.1999.1869     Document Type: Article

References (25)

1. Anderson T. W. Estimating linear statistical relationships. Ann. Statist. 12:1984;1-45.
2. Bound J., Krueger A. B. The extend of measurement error in longitudinal earning data: Do two wrongs make a right? J. Labor Economics. 9:1989;1-24.
3. Buckley J., James L. Linear regression with censored data. Biometrika. 66:1979;429-436.
4. J. P. Buonaccorsic, Measurement error in the response in the general linear model, J. Amer. Statist. Assoc.91, No. , 633-642.
5. Carroll R. J., Wand M. P. Semiparametric estimation in logistic measure error models. J. Roy. Statist. Ass. Ser. B. 53:1991;652-663.
6. Chen K. N., Lo S. H. On the rate of uniform convergence of the product-limit estimator: Strong and weak laws. Ann Statist. 25:1997;613-641.
7. Fuller W. A. Properties of some estimators for error-in-variables model. Ann. Statist. 8:1980;407-422.
8. Gleser L. J. On the asymptotric theory of fixed size sequential confidence bounds for linear regression parameters. Ann. Math. Statist. 36:1965;463-467.
9. Gallo P. P. Properties of Estimators in Error-in-Variables Regression Models. 1982;University of North Carolina, Chapel Hill.
10. Healy J. D. Maximum likelihood estimation of a multivariate linear functional relationship. J. Multivariate. Anal. 10:1980;243-251.
11. James I. R., Smith P. J. Consistency results for linear regression with censored data. Ann. Statist. 12:1984;590-600.
12. Lai T. L., Ying Z. Large sample theory of a modified Buckley-James estimator for regression analysis with censored data. Ann. Statist. 19:1991;1370-1402.
13. Miller R. G. Least squares regression with censored data. Biometrika. 69:1976;449-464.
14. Pepe M. S. Inference using surrogate outcome data and a validation sample. Biometrika. 79:1992;355-365.
15. Pepe M. S., Fleming T. R. A general nonparametric method for dealing with errors in missing or surrogate covariate data. J. Amer. Statist. Assoc. 86:1991;108-113.
16. Prakasa Rao B. L. S. Asymptotic Theory of Statistical Inference. 1987;Wiley, New York.
17. Prentice R. L. Surrogate endpoints in clinical trials: definition and operational oriteria. Statist. Med. 8:1989;431-440.
18. Ritov Y. Estimation in linear regression model with censored data. Ann. Statist. 18:1990;303-328.
19. Sepanski J. H., Lee L. F. Semiparametric Estimation of nonlinear error-in-variables models with validation study. J. Nonparametr. Statist. 4:1995;365-394.
20. Srinivasan C., Zhou M. Linear regression with censoring. J. Multivariate Anal. 49:1994;179-201.
21. Stute W. Strong and weak representation of cumulative hazard function and Kaplan-Meier estimators on increasing sets. J. Statist. Plann. Inference. 42:1994;315-329.
22. Susarla, Ryzin. Regression analysis with randomly right censored data. Ann. Statist. 9:1981;1276-1288.
23. Wang Q. H. Estimation of partial linear error-in-variables models with validation data. J. Multivariate Anal. 69:1999;30-64.
24. Q. H. Wang, Estimation of partial linear error-in-response models with validation data, Manuscript, 1997.
25. Wittes J., Lakatos E., Probstfield J. Surrogate endpoints in clinical trials: Cardiovascular diseases. Statist. Med. 8:1989;415-425.