On the identifiability of copulas in bivariate competing risks models |
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Authors: | Maik Schwarz Geurt Jongbloed Ingrid Van Keilegom |
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Institution: | 1. Institut de statistique, biostatistique et sciences actuarielles, Université catholique de Louvain, Louvain‐la‐Neuve, Belgium;2. Delft Institute of Applied Mathematics, Delft University of Technology, Delft, The Netherlands |
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Abstract: | In competing risks models, the joint distribution of the event times is not identifiable even when the margins are fully known, which has been referred to as the “identifiability crisis in competing risks analysis” (Crowder, 1991). We model the dependence between the event times by an unknown copula and show that identification is actually possible within many frequently used families of copulas. The result is then extended to the case where one margin is unknown. The Canadian Journal of Statistics 41: 291–303; 2013 © 2013 Statistical Society of Canada |
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Keywords: | Bivariate distribution competing risks copulas dependent censoring identification MSC 2010: Primary 62N01 secondary 62N99 |
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