SEMIPARAMETRIC REGRESSION WITH TIME-DEPENDENT COEFFICIENTS FOR FAILURE TIME DATA ANALYSIS

We propose a working independent profile likelihood method for the semiparametric time-varying coefficient model with correlation. Kernel likelihood is used to estimate time-varying coefficients. Profile likelihood for the parametric coefficients is formed by plugging in the nonparametric estimator. For independent data, the estimator is asymptotically normal and achieves the asymptotic semiparametric efficiency bound. We evaluate the performance of proposed nonparametric kernel estimator and the profile estimator, and apply the method to the western Kenya parasitemia data.