Mixed Discrete and Continuous Cox Regression Model
dc.contributor.author | Prentice, Ross L. | en_US |
dc.contributor.author | Kalbfleisch, John D. | en_US |
dc.date.accessioned | 2006-09-11T18:17:32Z | |
dc.date.available | 2006-09-11T18:17:32Z | |
dc.date.issued | 2003-06 | en_US |
dc.identifier.citation | Prentice, Ross L.; Kalbfleisch, John D.; (2003). "Mixed Discrete and Continuous Cox Regression Model." Lifetime Data Analysis 9(2): 195-210. <http://hdl.handle.net/2027.42/46860> | en_US |
dc.identifier.issn | 1380-7870 | en_US |
dc.identifier.issn | 1572-9249 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/46860 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=12735496&dopt=citation | en_US |
dc.description.abstract | The Cox (1972) regression model is extended to include discrete and mixed continuous/discrete failure time data by retaining the multiplicative hazard rate form of the absolutely continuous model. Application of martingale arguments to the regression parameter estimating function show the Breslow (1974) estimator to be consistent and asymptotically Gaussian under this model. A computationally convenient estimator of the variance of the score function can be developed, again using martingale arguments. This estimator reduces to the usual hypergeometric form in the special case of testing equality of several survival curves, and it leads more generally to a convenient consistent variance estimator for the regression parameter. A small simulation study is carried out to study the regression parameter estimator and its variance estimator under the discrete Cox model special case and an application to a bladder cancer recurrence dataset is provided. | en_US |
dc.format.extent | 133526 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Statistics | en_US |
dc.subject.other | Statistics, General | en_US |
dc.subject.other | Statistics for Business/Economics/Mathematical Finance/Insurance | en_US |
dc.subject.other | Statistics for Life Sciences, Medicine, Health Sciences | en_US |
dc.subject.other | Quality Control, Reliability, Safety and Risk | en_US |
dc.subject.other | Operation Research/Decision Theory | en_US |
dc.subject.other | Cox Regression | en_US |
dc.subject.other | Counting Process | en_US |
dc.subject.other | Martingale | en_US |
dc.subject.other | Tied Failure Times | en_US |
dc.title | Mixed Discrete and Continuous Cox Regression Model | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Mathematics | en_US |
dc.subject.hlbsecondlevel | Statistics and Numeric Data | en_US |
dc.subject.hlbtoplevel | Social Sciences | 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, MI, 48109, USA | en_US |
dc.contributor.affiliationother | Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA, 98109, USA | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.identifier.pmid | 12735496 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/46860/1/10985_2004_Article_5119440.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1022935019768 | en_US |
dc.identifier.source | Lifetime Data Analysis | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.