Estimation by polynomial splines with variable selection in additive Cox models

In this article, we consider penalized variable selection in additive Cox models based on (group) smoothly clipped absolute deviation penalty and hence widen the scope of applicability of penalized variable selection to semiparametric models for censored data. We demonstrate the asymptotic consistency in model selection and convergence rate in estimation. Our simulation study emphasizes comparison of several different criteria for tuning parameter selection and also compares two appropriate definitions of the degrees of freedom in additive models.