A model selection test for bivariate failure-time data

In this paper, we address two important issues in semiparametric survival model selection for censored data generated by the Archimedean copula family: method of estimating the parametric copulas and data reuse. We demonstrate that for selection among candidate copula models that could all be misspecified, estimators of the para-metric copulas based on minimizing the selection criterion function may be preferred to other estimators. To handle the issue of data reuse, we put model selection in the context of hypothesis testing and propose a simple test for model selection from a fi-nite number of parametric copulas. Results from a simulation study and two empirical applications provide strong support to our theoretical findings