A semiparametric recurrent events model with time‐varying coefficients. (18th August 2012) - Yu, Zhangsheng; Liu, Lei; Bravata, Dawn M.; Williams, Linda S.; Tepper, Robert S.
<x xml:space="preserve">Abstract</x> We consider a recurrent events model with time‐varying coefficients motivated by two clinical applications. We use a random effects (Gaussian frailty) model to describe the intensity of recurrent events. The model can accommodate both time‐varying and time‐constant coefficients. We use the penalized spline method to estimate the time‐varying coefficients. We use Laplace approximation to evaluate the penalized likelihood without a closed form. We estimate the smoothing parameters in a similar way to variance components. We conduct simulations to evaluate the performance of the estimates for both time‐varying and time‐independent coefficients. We apply this method to analyze two data sets: a stroke study and a child wheeze study. Copyright © 2012 John Wiley & Sons, Ltd.