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[ZFL11] Competing risks regression for clustered dataRevue Internationale avec comité de lecture : Journal Biostatistics, vol. 13(3), pp. 371-83, 2011, (doi:10.1093/biostatistics/kxr032)
motcle:
Résumé:
A population average regression model is proposed to assess the marginal effects of covariates
on the cumulative incidence function when there is dependence across individuals
within a cluster in the competing risks setting. This method extends the Fine–Gray model proportional hazards
model for the subdistribution to situations where individualswithin a cluster may be correlated due to unobserved shared factors.
Estimators of the regression parameters in the marginal model are developed under an independence
working assumption, where the correlation across individuals within a cluster is
completely unspecified. The estimators are consistent and asymptotically normal, and
variance estimation may be achieved without specifying the form of the dependence
across individuals. A simulation study evidences that the inferential procedures perform
well with realistic sample sizes. The practical utility of the methods is illustrated with
data from the European Bone Marrow Transplant Registry.
Commentaires:
R package crrSC
http://cran.r-project.org/web/packages/crrSC/index.html
Equipe:
msdma
BibTeX
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