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Archimedean copula model selection under dependent truncation
Author(s) -
Beaudoin D.,
LakhalChaieb L.
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3316
Subject(s) - copula (linguistics) , mathematics , truncation (statistics) , multivariate statistics , statistics , econometrics
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.