Estimation in a Cox Proportional Hazards Cure Model
dc.contributor.author | Sy, Judy P. | en_US |
dc.contributor.author | Taylor, Jeremy M. G. | en_US |
dc.date.accessioned | 2010-04-01T15:25:22Z | |
dc.date.available | 2010-04-01T15:25:22Z | |
dc.date.issued | 2000-03 | en_US |
dc.identifier.citation | Sy, Judy P.; Taylor, Jeremy M. G. (2000). "Estimation in a Cox Proportional Hazards Cure Model." Biometrics 56(1): 227-236. <http://hdl.handle.net/2027.42/65901> | en_US |
dc.identifier.issn | 0006-341X | en_US |
dc.identifier.issn | 1541-0420 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/65901 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=10783800&dopt=citation | en_US |
dc.description.abstract | Some failure time data come from a population that consists of some subjects who are susceptible to and others who are nonsusceptible to the event of interest. The data typically have heavy censoring at the end of the follow-up period, and a standard survival analysis would not always be appropriate. In such situations where there is good scientific or empirical evidence of a nonsusceptible population, the mixture or cure model can be used (Farewell, 1982, Biometrics 38 , 1041–1046). It assumes a binary distribution to model the incidence probability and a parametric failure time distribution to model the latency. Kuk and Chen (1992, Biometrika 79 , 531–541) extended the model by using Cox's proportional hazards regression for the latency. We develop maximum likelihood techniques for the joint estimation of the incidence and latency regression parameters in this model using the nonparametric form of the likelihood and an EM algorithm. A zero-tail constraint is used to reduce the near nonidentifiability of the problem. The inverse of the observed information matrix is used to compute the standard errors. A simulation study shows that the methods are competitive to the parametric methods under ideal conditions and are generally better when censoring from loss to follow-up is heavy. The methods are applied to a data set of tonsil cancer patients treated with radiation therapy. | en_US |
dc.format.extent | 915282 bytes | |
dc.format.extent | 3110 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.publisher | Blackwell Publishing Ltd | en_US |
dc.rights | The International Biometric Society, 2000 | en_US |
dc.subject.other | Cure Model | en_US |
dc.subject.other | EM Algorithm | en_US |
dc.subject.other | Product-limit Estimate | en_US |
dc.subject.other | Profile Likelihood | en_US |
dc.title | Estimation in a Cox Proportional Hazards Cure Model | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Mathematics | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, U.S.A. email: jmgt@umich.edu | en_US |
dc.contributor.affiliationother | Biostatistics, Genentech Inc., 1 DNA Way, South San Francisco, California 94080, U.S.A. | en_US |
dc.identifier.pmid | 10783800 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/65901/1/j.0006-341X.2000.00227.x.pdf | |
dc.identifier.doi | 10.1111/j.0006-341X.2000.00227.x | en_US |
dc.identifier.source | Biometrics | en_US |
dc.identifier.citedreference | Andersen, P. K. and Gill, R. D. ( 1982 ). Cox's regression model for counting processes: A large sample study. Annals of Statistics 10, 1100 – 1120. | en_US |
dc.identifier.citedreference | Bailey, K. R. ( 1984 ). Asymptotic equivalence between the Cox estimator and the general ML estimators of regression and survival parameters in the Cox model. Annals of Statistics 12, 730 – 736. | en_US |
dc.identifier.citedreference | Breslow, N. E. ( 1972 ). Contribution to the discussion of D. R. Cox ( 1972 ). Journal of the Royal Statistical Society, Series B 34, 216 – 217. | en_US |
dc.identifier.citedreference | Farewell, V. T. ( 1982 ). The use of mixture models for the analysis of survival data with long-term survivors. Biometrics 38, 1041 – 1046. | en_US |
dc.identifier.citedreference | Farewell, V. T. ( 1986 ). Mixture models in survival analysis: Are they worth the risk ? Canadian Journal of Statistics 14, 257 – 262. | en_US |
dc.identifier.citedreference | Kalbfleisch, J. D. and Prentice, R. L. ( 1980 ). The Statistical Analysis of Failure Time Data. New York : Wiley. | en_US |
dc.identifier.citedreference | Klein, J. P. ( 1992 ). Semiparametric estimation of random effects using the Cox model based on the EM algorithm. Biometrics 48, 795 – 806. | en_US |
dc.identifier.citedreference | Kuk, A. Y. C. and Chen, C. H. ( 1992 ). A mixture model combining logistic regression with proportional hazards regression. Biometrika 79, 531 – 541. | en_US |
dc.identifier.citedreference | Louis, T. A. ( 1982 ). Finding the observed information matrix when using the EM algorithm. Journal of the Royal Statistical Society, Series B 44, 226 – 233. | en_US |
dc.identifier.citedreference | Mailer, R. A. and Zhou, S. ( 1996 ). Survival Analysis with Long Term Survivors. New York : Wiley. | en_US |
dc.identifier.citedreference | Peng, Y., Dear, K. B. G., and Denham, J. W. ( 1998 ). A generalized F mixture model for cure rate estimation. Statistics in Medicine 17, 813 – 830. | en_US |
dc.identifier.citedreference | Prentice, R. L. and Gloeckler, L. A. ( 1978 ). Regression analysis of grouped survival data with application to breast cancer data. Biometrics 34, 57 – 67. | en_US |
dc.identifier.citedreference | Sy, J. P. and Taylor, J. M. G. ( 1999 ). Standard errors for the Cox proportional hazards curve model. Mathematical and Computer Modelling, in press. | en_US |
dc.identifier.citedreference | Taylor, J. M. G. ( 1995 ). Semi-parametric estimation in failure time mixture models. Biometrics 51, 899 – 907. | en_US |
dc.identifier.citedreference | Tsiatis, A. A. ( 1981 ). A large sample study of Cox's regression model. Annals of Statistics 9, 93 – 108. | en_US |
dc.identifier.citedreference | Withers, H. R., Peters, L. J., Taylor, J. M. G., et al. ( 1995 ). Local control of carcinoma of the tonsil by radiation therapy: An analysis of patterns of fractionation in nine institutions. International Journal of Radiation Oncology, Biology, Physics 33, 549 – 562. | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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