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dc.date.accessioned2013-03-12T08:17:41Z
dc.date.available2013-03-12T08:17:41Z
dc.date.issued2002en_US
dc.date.submitted2011-07-08en_US
dc.identifier.urihttp://hdl.handle.net/10852/10299
dc.description.abstractMulti-state models are used to describe situations where individuals may move among a finite number of states defined by specific conditions of health, including death. The transition intensities of the models are described by proportional hazards models, and it is reviewed how estimation of the regression parameters and the baseline transition intensities may be performed when only nested case-control data are available for all or some of the transitions. The regression parameter estimates and the estimates of baseline transition intensities are combined to give estimates of the integrated transition intensities for specified covariate histories, and from these estimates covariate-dependent Markov transition probabilities are derived.eng
dc.language.isoengen_US
dc.publisherMatematisk Institutt, Universitetet i Oslo
dc.relation.ispartofPreprint series. Statistical Research Report http://urn.nb.no/URN:NBN:no-23420en_US
dc.relation.urihttp://urn.nb.no/URN:NBN:no-23420
dc.titleEstimation of covariate-dependent Markov transition probabilities from nested case-control dataen_US
dc.typeResearch reporten_US
dc.date.updated2011-07-08en_US
dc.creator.authorBorgan, Ørnulfen_US
dc.subject.nsiVDP::410en_US
dc.identifier.urnURN:NBN:no-28244en_US
dc.type.documentForskningsrapporten_US
dc.identifier.duo132076en_US
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/10299/1/stat-res-01-02.pdf


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