Archimedean copula model selection under dependent truncation

One‐sided truncated survival data arise when a pair of time‐to‐event variables ( X, Y ) is observed only when X < Y . Existing methods of analysis rely on the assumption of quasi‐independence between X and Y . Recently, Lakhal‐Chaieb et al. ( Biometrika 2006; 93 :655–669) modeled potential dependency between these random variables via a semi‐survival Archimedean copula. In this paper, we present a model selection procedure to rank a set of semi‐survival Archimedean copula families according to their ability to fit a given data set subject to dependent truncation. The proposed procedure is based on a truncated version of Kendall's tau ( J. Multivariate Anal . 1996; 56 :60–74). The performance of the proposal is illustrated through simulations and three real data sets. Copyright © 2008 John Wiley & Sons, Ltd.