Title of article :
Semiparametric Analysis of Recurrent Events Data in the Presence of Dependent Censoring
Author/Authors :
D.، Ghosh نويسنده , , D.Y.، Lin نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2003
Pages :
-876
From page :
877
To page :
0
Abstract :
Dependent censoring occurs in longitudinal studies of recurrent events when the censoring time depends on the potentially unobserved recurrent event times. To perform regression analysis in this setting, we propose a semiparametric joint model that formulates the marginal distributions of the recurrent event process and dependent censoring time through scale-change models, while leaving the distributional form and dependence structure unspecified. We derive consistent and asymptotically normal estimators for the regression parameters. We also develop graphical and numerical methods for assessing the adequacy of the proposed model. The finite-sample behavior of the new inference procedures is evaluated through simulation studies. An application to recurrent hospitalization data taken from a study of intravenous drug users is provided.
Keywords :
Multiple events , Competing risks , Counting process , Accelerated failure time model , Empirical process , survival analysis
Journal title :
BIOMETRICS (BIOMETRIC SOCIETY)
Serial Year :
2003
Journal title :
BIOMETRICS (BIOMETRIC SOCIETY)
Record number :
84197
Link To Document :
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