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dc.contributor.authorEl Barmi, Hammou
dc.contributor.authorMukerjee, Hari
dc.date.accessioned2012-06-21T13:40:18Z
dc.date.available2012-06-21T13:40:18Z
dc.date.issued2006
dc.identifier.citationBarmi, H. E. and H. Mukerjee (2006). "Restricted Estimation of the Cumulative Incidence Functions Corresponding to Competing Risks." Lecture Notes-Monograph Series 49: Optimality: The Second Erich L. Lehmann Symposium , 241-252.en_US
dc.identifier.issn0749-2170
dc.identifier.urihttp://hdl.handle.net/10057/5201
dc.identifier.urihttp://dx.doi.org/10.1214/074921706000000482
dc.identifier.urihttp://projecteuclid.org/euclid.lnms/1196283964
dc.descriptionOpen accessen_US
dc.description.abstractIn the competing risks problem, an important role is played by the cumulative incidence function (CIF), whose value at time t is the probability of failure by time t from a particular type of failure in the presence of other risks. In some cases there are reasons to believe that the CIFs due to various types of failure are linearly ordered. El Barmi et al. [3] studied the estimation and inference procedures under this ordering when there are only two causes of failure. In this paper we extend the results to the case of k CIFs, where k > 3. Although the analyses are more challenging, we show that most of the results in the 2-sample case carry over to this fc-sample case.en_US
dc.language.isoen_USen_US
dc.publisherInstitute of Mathematical Statisticsen_US
dc.relation.ispartofJavier Rojo, ed., Optimality: The Second Erich L. Lehmann Symposium (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2006), 241-252.
dc.relation.ispartofseriesLecture Notes-Monograph Series;v.49
dc.subjectCompeting risksen_US
dc.subjectCumulative incidence functions
dc.subjectEstimation
dc.subjectHypothesis test
dc.subjectFc-sample problems
dc.subjectOrder restriction
dc.subjectWeak convergence
dc.titleRestricted estimation of the cumulative incidence functions corresponding to competing risksen_US
dc.typeArticleen_US
dc.description.versionPeer reviewed
dc.rights.holderCopyright © 2006 Institute of Mathematical Statistics


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