Lifetime Data Anal - A copula model for marked point processes.

Tópicos

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Resumo

Many 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.

Resumo Limpo

mani chronic diseas featur recur clinic import event addit howev often exist random variabl realiz upon occurr event reflect sever event cost associ possibl short term respons indic effect therapeut intervent describ novel model mark point process incorpor depend continu mark event process use copula function copula formul ensur event time can model intens function point process multivari model can specifi continu mark relat effici joint versus separ analys event time mark examin simul random censor applic data recent trial transfus medicin given illustr

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