© 1982 by Biometrika Trust
Covariate measurement errors and parameter estimation in a failure time regression model
Fred Hutchinson Cancer Research Center Seattle, Washington, U.S.A.
Estimation in Cox's failure time regression model is considered when the regression vector is subject to measurement error. A hazard function model is induced for the failure rate given the measured covariate and a partial likelihood function is derived for the relative risk parameters. This partial likelihood function may involve the baseline hazard function as well as the regression parameter, but useful inference techniques arise for testing whether the regression parameter equals zero and for more general inferences in important special cases. Explicit consideration is given to testing equality of survival curves when group membership is subject to misclassification and to relative risk estimation with normally distributed covariates. Approaches to regression estimation using the overall likelihood function, and a marginal likelihood function based on failure time ranks, are also indicated. Illustration of the possible effect of covariate errors on relative risk estimation is provided.
Key Words: Censoring • Classification error • Covariate error • Failure time • Hazard function • Log rank test • Marginal likelihood • Partial likelihood • Proportional hazards model • Regression • Relative risk
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  S. Fieuws, G. Verbeke, B. Maes, and Y. Vanrenterghem Predicting renal graft failure using multivariate longitudinal profiles Biostat., July 1, 2008; 9(3): 419 - 431. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. Y. Yi A simulation-based marginal method for longitudinal data with dropout and mismeasured covariates Biostat., July 1, 2008; 9(3): 501 - 512. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Z. Fewell, G. Davey Smith, and J. A. C. Sterne The Impact of Residual and Unmeasured Confounding in Epidemiologic Studies: A Simulation Study Am. J. Epidemiol., September 15, 2007; 166(6): 646 - 655. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. E. Andersen, O. Raaschou-Nielsen, H. P. Andersen, M. Lind, P. Gravesen, B. L. Thomsen, and K. Ulbak Prediction of 222Rn in Danish dwellings using geology and house construction information from central databases Radiat Prot Dosimetry, January 1, 2007; 123(1): 83 - 94. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Lamina, C. Meisinger, I. M. Heid, H. Lowel, B. Rantner, W. Koenig, F. Kronenberg, and for the KORA Study Group Association of ankle-brachial index and plaques in the carotid and femoral arteries with cardiovascular events and total mortality in a population-based study with 13 years of follow-up Eur. Heart J., November 1, 2006; 27(21): 2580 - 2587. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 O. Reksen, L. Solverod, A. J. Branscum, and O. Osteras Relationships between milk culture results and treatment for clinical mastitis or culling in Norwegian dairy cattle. J Dairy Sci, August 1, 2006; 89(8): 2928 - 2937. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 H.-M. KIM, Y. YASUI, and I. BURSTYN Attenuation in Risk Estimates in Logistic and Cox Proportional-Hazards Models due to Group-Based Exposure Assessment Strategy Ann. Hyg., August 1, 2006; 50(6): 623 - 635. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. Chen, W. Lin, F. Shen, U. H Iloeje, W T. London, and A. A Evans Chronic hepatitis B virus infection and mortality from non-liver causes: results from the Haimen City cohort study Int. J. Epidemiol., February 1, 2005; 34(1): 132 - 137. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. A Bennett Review of analytical methods for prospective cohort studies using time to event data: single studies and implications for meta-analysis Statistical Methods in Medical Research, August 1, 2003; 12(4): 297 - 319. [Abstract] [PDF]
|
|
|
|
 |
|
 A. A. Evans, G. Chen, E. A. Ross, F.-M. Shen, W.-Y. Lin, and W. T. London Eight-Year Follow-Up of the 90,000-Person Haimen City Cohort: I. Hepatocellular Carcinoma Mortality, Risk Factors, and Gender Differences Cancer Epidemiol. Biomarkers Prev., April 1, 2002; 11(4): 369 - 376. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. E. Halloran and I. M. Longini Jr. Using Validation Sets for Outcomes and Exposure to Infection in Vaccine Field Studies Am. J. Epidemiol., September 1, 2001; 154(5): 391 - 398. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
O. Raaschou-Nielsen, O. Hertel, B. L. Thomsen, and J. H. Olsen Air Pollution from Traffic at the Residence of Children with Cancer Am. J. Epidemiol., March 1, 2001; 153(5): 433 - 443. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. E. Hankinson, W. C. Willett, D. S. Michaud, J. E. Manson, G. A. Colditz, C. Longcope, B. Rosner, and F. E. Speizer Plasma Prolactin Levels and Subsequent Risk of Breast Cancer in Postmenopausal Women J Natl Cancer Inst, April 7, 1999; 91(7): 629 - 634. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. L. Prentice Design issues in cohort studies Statistical Methods in Medical Research, December 1, 1995; 4(4): 273 - 292. [Abstract] [PDF]
|
|
|
|
 |
|
 E Lindenstrom, G Boysen, and J Nyboe Influence of total cholesterol, high density lipoprotein cholesterol, and triglycerides on risk of cerebrovascular disease: the Copenhagen city heart study BMJ, July 2, 1994; 309(6946): 11 - 15. [Abstract] [Full Text]
|
|