A semiparametric recurrent events model with time-varying coefficients.
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.
Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, USA. yuz@iupui.edu
Zhangsheng
Z
Yu
Lei
L
Liu
Dawn M
DM
Bravata
Linda S
LS
Williams
Robert S
RS
Tepper
D001249:Asthma / Q000209:etiology; D002675:Child, Preschool; D002986:Clinical Trials as Topic / Q000379:methods*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D015233:Models, Statistical; D012135:Respiratory Sounds / Q000209:etiology