Model Selection and Semiparametric Inference for Bivariate Failure-Time Data

Abstract We propose model selection procedures for bivariate survival models for censored data generated by the Archimedean copula family. In route to constructing the selection methodology, we develop estimates of some time-dependent association measures, including estimates of the local and global Kendall's tau, local odds ratio, and other measures defined throughout the literature. We propose a goodness-of-fit-based model selection methodology as well as a graphical approach. We show that the proposed methods have desirable asymptotic properties and perform well in finite samples.