Using Auxiliary Time-Dependent Covariates to Recover Information in Nonparametric Testing with Censored Data
dc.contributor.author | Murray, Susan | en_US |
dc.contributor.author | Tsiatis, Anastasios A. | en_US |
dc.date.accessioned | 2006-09-11T18:15:59Z | |
dc.date.available | 2006-09-11T18:15:59Z | |
dc.date.issued | 2001-06 | en_US |
dc.identifier.citation | Murray, Susan; Tsiatis, Anastasios A.; (2001). "Using Auxiliary Time-Dependent Covariates to Recover Information in Nonparametric Testing with Censored Data." Lifetime Data Analysis 7(2): 125-141. <http://hdl.handle.net/2027.42/46839> | en_US |
dc.identifier.issn | 1380-7870 | en_US |
dc.identifier.issn | 1572-9249 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/46839 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=11458653&dopt=citation | en_US |
dc.description.abstract | Murrayand Tsiatis (1996) described a weighted survival estimate thatincorporates prognostic time-dependent covariate informationto increase the efficiency of estimation. We propose a test statisticbased on the statistic of Pepe and Fleming (1989, 1991) thatincorporates these weighted survival estimates. As in Pepe andFleming, the test is an integrated weighted difference of twoestimated survival curves. This test has been shown to be effectiveat detecting survival differences in crossing hazards settingswhere the logrank test performs poorly. This method uses stratifiedlongitudinal covariate information to get more precise estimatesof the underlying survival curves when there is censored informationand this leads to more powerful tests. Another important featureof the test is that it remains valid when informative censoringis captured by the incorporated covariate. In this case, thePepe-Fleming statistic is known to be biased and should not beused. These methods could be useful in clinical trials with heavycensoring that include collection over time of covariates, suchas laboratory measurements, that are prognostic of subsequentsurvival or capture information related to censoring. | en_US |
dc.format.extent | 169781 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 | Kaplan-Meier Estimate | en_US |
dc.subject.other | Longitudinal | en_US |
dc.subject.other | Missing Data | en_US |
dc.subject.other | Survival | en_US |
dc.subject.other | Two-sample Test | en_US |
dc.title | Using Auxiliary Time-Dependent Covariates to Recover Information in Nonparametric Testing with Censored Data | 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 | Science | en_US |
dc.subject.hlbtoplevel | Social Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109-2029 | en_US |
dc.contributor.affiliationother | North Carolina State University, Raleigh, NC, 27695-8203 | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.identifier.pmid | 11458653 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/46839/1/10985_2004_Article_335514.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1011392622173 | en_US |
dc.identifier.source | Lifetime Data Analysis | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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