On the testability of the CAR assumption

dc.creatorCator, Eric A.
dc.date2005-03-31
dc.date.accessioned2026-07-07T08:06:48Z
dc.date.available2026-07-07T08:06:48Z
dc.descriptionIn recent years a popular nonparametric model for coarsened data is an assumption on the coarsening mechanism called coarsening at random (CAR). It has been conjectured in several papers that this assumption cannot be tested by the data, that is, the assumption does not restrict the possible distributions of the data. In this paper we will show that this conjecture is not always true; an example will be current status data. We will also give conditions when the conjecture is true, and in doing so, we will introduce a generalized version of the CAR assumption. As an illustration, we retrieve the well-known result that the CAR assumption cannot be tested in the case of right-censored data.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053604000000418 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0503737
dc.identifierhttp://arxiv.org/abs/math/0503737
dc.identifierAnnals of Statistics 2004, Vol. 32, No. 5, 1957-1980
dc.identifierdoi:10.1214/009053604000000418
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130732
dc.subjectStatistics Theory
dc.subject62A10, 62F10. (Primary)
dc.titleOn the testability of the CAR assumption
dc.typetext

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