The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Covariate measurement errors and parameter estimation in a failure time regression model
Abstract
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.
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Cites
Asymptotically Efficient Rank Invariant Test Procedures
Peto, R., & Peto, J. (1972) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344317 · Cited by 3,393
Covariance Analysis of Censored Survival Data
Breslow, N. (1974) · Biometrics · doi:10.2307/2529620 · Cited by 1,763
The Efficiency of Cox's Likelihood Function for Censored Data
Efron, B. (1977) · Journal of the American Statistical Association · doi:10.1080/01621459.1977.10480613 · Cited by 1,228
Marginal likelihoods based on Cox's regression and life model
KALBFLEISCH, J. D., & PRENTICE, R. L. (1973) · Biometrika · doi:10.1093/biomet/60.2.267 · Cited by 537
Self-citationErrors of Measurement in Statistics
Cochran, W. G. (1968) · Technometrics · doi:10.1080/00401706.1968.10490621 · Cited by 479
A Large Sample Study of Cox's Regression Model
Tsiatis, A. A. (1981) · The Annals of Statistics · doi:10.1214/aos/1176345335 · Cited by 476
Cited by
Chambless, L. E., Heiss, G., Folsom, A. R., Rosamond, W., Szklo, M., Sharrett, A. R., & Clegg, L. X. (1997) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009302 · Cited by 1,990
The Impact of Residual and Unmeasured Confounding in Epidemiologic Studies: A Simulation Study
Fewell, Z., Davey Smith, G., & Sterne, J. A. C. (2007) · American Journal of Epidemiology · doi:10.1093/aje/kwm165 · Cited by 734
Neaton, J. D. (1992) · Archives of Internal Medicine · doi:10.1001/archinte.1992.00400130082009 · Cited by 784
Freedman, L. S., Commins, J. M., Moler, J. E., Arab, L., Baer, D. J., Kipnis, V., Midthune, D., Moshfegh, A. J., Neuhouser, M. L., Prentice, R. L., et al. (2014) · American Journal of Epidemiology · doi:10.1093/aje/kwu116 · Cited by 528
Self-citationLindenstrom, E., Boysen, G., & Nyboe, J. (1994) · BMJ · doi:10.1136/bmj.309.6946.11 · Cited by 370
Metadata
- Authors
- PRENTICE, R. L.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1982
- Volume
- 69
- Issue
- 2
- Pages
- 331-342
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W1993373433
- Cited by
- 668
- References
- 6
- FWCI
- 3.32
- Type
- journal article
- Language
- en
- Open access
- closed
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