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dc.contributor.authorLawless, Jerald F.
dc.contributor.authorCook, Richard J.
dc.date.accessioned2020-03-11 17:20:48 (GMT)
dc.date.available2020-03-11 17:20:48 (GMT)
dc.date.issued2019-07-24
dc.identifier.urihttps://doi.org/10.1002/sim.8318
dc.identifier.urihttp://hdl.handle.net/10012/15690
dc.descriptionThis is the peer reviewed version of the following article: Jerald F. Lawless and Richard J. Cook, A new perspective on loss to follow-up in failure time and life history studies. Statistics in Medicine (2019), 38(23): 4583–4610 which has been published in final form at https://doi.org/10.1002/sim.8318.en
dc.description.abstractA framework is proposed for the joint modeling of life history and loss to follow-up (LTF) processes in cohort studies. This framework provides a basis for discussing independence conditions for LTF and censoring and examining the implications of dependent LTF.We consider failure time and more general life history processes. The joint models are based on multistate processes with expanded state spaces encompassing both the life history and LTF processes. Tracing studies are discussed as a means of investigating the presence of dependent censoring and providing valid estimates of transition intensities and state occupancy probabilities. Simulation studies and an illustration based on a cohort of individuals with systemic lupus erythematosus demonstrate the usefulness and properties of the proposed methods.en
dc.description.sponsorshipFunding was provided by the Natural Sciences and Engineering Research Council of Canada (RGPIN 8597 for JFL; RGPIN 155849 and RGPIN 04207 for RJC) and the Canadian Institutes of Health Research (FRN 13887 for RJC).en
dc.language.isoenen
dc.publisherWileyen
dc.relation.ispartofseriesStatistics in Medicine;
dc.subjectauxiliary dataen
dc.subjectindependent censoringen
dc.subjectlife history processen
dc.subjectloss to follow-upen
dc.subjectmultistate modelen
dc.subjecttracing studiesen
dc.titleA new perspective on loss to follow-up in failure time and life history studiesen
dc.typeArticleen
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2Statistics and Actuarial Scienceen
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen


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