A Model Selection Test for Bivariate Failure-Time Data
Working Paper No. 04-W21
Xiaohong Chen and Yanqin Fan
ABSTRACT [article]
In this paper, we address two important issues in 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
model selection, estimators of the parametric 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
finite number of parametric copulas. Results from a simulation study and
two empirical applications provide strong support to our theoretical findings.
Keywords and Phrases: Archimedean copula, bivariate survival function, data reuse,
minimum-distance estimation, model selection
JEL Classification Number: C14, C34, C52