A Combined GEE/Buckley-James Method for Estimating an Accelerated Failure Time Model of Multivariate Failure Times
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vor 28 Jahren
The present paper deals with the estimation of a frailty model of
multivariate failure times. The failure times are modeled by an
Accelerated Failure Time Model including observed covariates and an
unobservable frailty component. The frailty is assumed random and
differs across elementary units, but is constant across the spells
of a unit or a group. We develop an estimator (of the regression
parameters) that combines the GEE approach (Liang and Zeger, 1986)
with the Buckley-James estimator for censored data. This estimator
is robust against violations of the correlation structure and the
distributional assumptions. Some simulation studies are conducted
in order to study the empirical performance of the estimator.
Finally, the methods are applied to data of repeated appearances of
malign ventricular arrhythmias at patients with implanted
defibrillator.
multivariate failure times. The failure times are modeled by an
Accelerated Failure Time Model including observed covariates and an
unobservable frailty component. The frailty is assumed random and
differs across elementary units, but is constant across the spells
of a unit or a group. We develop an estimator (of the regression
parameters) that combines the GEE approach (Liang and Zeger, 1986)
with the Buckley-James estimator for censored data. This estimator
is robust against violations of the correlation structure and the
distributional assumptions. Some simulation studies are conducted
in order to study the empirical performance of the estimator.
Finally, the methods are applied to data of repeated appearances of
malign ventricular arrhythmias at patients with implanted
defibrillator.
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