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dc.contributor.authorDiao, Liqun
dc.contributor.authorCook, Richard J.
dc.contributor.authorLee, Ker-Ai 18:33:10 (GMT) 18:33:10 (GMT)
dc.descriptionThe final publication (Diao, Liqun, Richard J. Cook, and Ker-Ai Lee. (2013) A copula model for marked point processes. Lifetime Data Analysis, 19(4): 463-489) is available at Springer via
dc.description.abstractMany chronic diseases feature recurring clinically important events. In addition, however, there often exists a random variable which is realized upon the occurrence of each event reflecting the severity of the event, a cost associated with it, or possibly a short term response indicating the effect of a therapeutic intervention. We describe a novel model for a marked point process which incorporates a dependence between continuous marks and the event process through the use of a copula function. The copula formulation ensures that event times can be modeled by any intensity function for point processes, and any multivariate model can be specified for the continuous marks. The relative efficiency of joint versus separate analyses of the event times and the marks is examined through simulation under random censoring. An application to data from a recent trial in transfusion medicine is given for illustration.en
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626)en
dc.relation.ispartofseriesLifetime Data Analysis;19(4)en
dc.subjectcopula functionen
dc.subjectjoint analysisen
dc.subjectrecurrent eventsen
dc.titleA copula model for marked point processesen
dcterms.bibliographicCitationDiao, Liqun, Richard J. Cook, and Ker-Ai Lee. A copula model for marked point processes. Lifetime Data Analysis 19.4 (2013): 463-489en
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2Statistics and Actuarial Scienceen

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