Smoothing spline frailty model Pang Du Statistics Department Virginia Tech Abstract
Frailty model has been a popular
tool to model heterogeneity of individuals in different
subpopulations. In the model, an individual's hazard rate depends
partly on a frailty term, which is an unobservable random variable and
assumed to act multiplicatively on the hazard. In this
presentation, we propose a penalized likelihood approach. Via the
minimization of a functional consisting of negative full log likelihood
and roughness penalty, the baseline hazard function and the frailties
are jointly estimated, one nonparametrically by smoothing splines and
the other parametrically with log normal distribution. The performance
of the model is demonstrated by empirical studies and real data
examples.
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