Yu, ZhangshengLiu, LeiBravata, Dawn M.Williams, Linda S.Tepper, Robert S.2016-10-072016-10-072013-03-15Yu, Z., Liu, L., Bravata, D. M., Williams, L. S., & Tepper, R. S. (2013). A Semiparametric Recurrent Events Model with Time-varying Coefficients. Statistics in Medicine, 32(6), 1016–1026. http://doi.org/10.1002/sim.55751097-0258https://hdl.handle.net/1805/11143We 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.en-USPublisher PolicyClinical Trials as TopicmethodsLikelihood FunctionsModels, StatisticalArticle