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.
Beaudoin
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Département des Opérations et Systèmes de Décision, Université Laval, Pavillon Palasis-Prince, 2325 rue de la terrasse, Québec, Qué., Canada G1V 0A6.
Lakhal-Chaieb
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D000163:Acquired Immunodeficiency Syndrome / Q000209:etiology; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003704:Dementia / Q000453:epidemiology / Q000401:mortality; D004812:Epidemiologic Methods; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis; D016008:Statistical Distributions; D018709:Statistics, Nonparametric; D016019:Survival Analysis; D065227:Transfusion Reaction