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dc.contributor.authorSeaman, Shaunen
dc.contributor.authorFarewell, Danielen
dc.contributor.authorDaniel, Rhianen
dc.date.accessioned2021-01-27T00:30:23Z
dc.date.available2021-01-27T00:30:23Z
dc.identifier.issn0006-3444
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/316750
dc.description.abstractWe offer a natural and extensible measure-theoretic treatment of missingness at random. Within the standard missing data framework, we give a novel characterization of the observed data as a stopping-set sigma algebra. We demonstrate that the usual missingness at random conditions are equivalent to requiring particular stochastic processes to be adapted to a set-indexed filtration. These measurability conditions ensure the usual factorization of likelihood ratios. We illustrate how the theory extends easily to incorporate explanatory variables, to describe longitudinal data in continuous time, and to admit more general coarsening of observations.
dc.publisherOxford University Press (OUP)
dc.rightsAll rights reserved
dc.titleMissing at random: a stochastic process perspectiveen
dc.typeArticle
prism.publicationNameBiometrikaen
dc.identifier.doi10.17863/CAM.63864
dcterms.dateAccepted2020-12-23en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2020-12-23en
dc.contributor.orcidSeaman, Shaun [0000-0003-3726-5937]
rioxxterms.typeJournal Article/Reviewen
cam.orpheus.counter43*
rioxxterms.freetoread.startdate2024-01-26


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