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DTSTAMP:20250806T080827Z
DESCRIPTION:Association Measures for Clustered Competing Risks Data\n\n\n	Ab
 stract:\n\n\nIn this work\, we propose a semiparametric model for multivar
 iate clustered competing risks data when the cause-specific failure times 
 and the occurrence of competing risk events among subjects within the same
  cluster are of interest. The cause-specific hazard functions are assumed 
 to follow Cox proportional hazard models\, and the associations between fa
 ilure times given the same or different cause events and the associations 
 between occurrences of competing risk events within the same cluster are i
 nvestigated through copula models. A cross-odds ratio measure is explored 
 under our proposed models. Two-stage estimation procedure is proposed in w
 hich the marginal models are estimated in the first stage\, and the depend
 ence parameters are estimated via an Expectation-Maximization algorithm in
  the second stage. The proposed estimators are shown to yield consistent a
 nd asymptotically normal under mild regularity conditions. Simulation stud
 ies are conducted to assess finite sample performance of the proposed meth
 od. The proposed technique is demonstrated through an application to a mul
 ticenter Bone Marrow transplantation dataset.\n
DTSTART:20180907T193000Z
DTEND:20180907T203000Z
LOCATION:Room 1104\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Chien-Lin (Mark) Su 
URL:/mathstat/channels/event/chien-lin-mark-su-289261
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